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GitHub - libxsmm/libxsmm: Library for specialized dense and sparse matrix operations, and deep learning primitives.
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17.9125 8.46625C18.6138 9.23625 19.04 10.2125 19.04 11.4225C19.04 15.6437 16.4688 16.5787 14.0213 16.8537C14.42 17.1975 14.7638 17.8575 14.7638 18.8887C14.7638 20.36 14.75 21.5425 14.75 21.9137C14.75 22.2025 14.9563 22.5462 15.5063 22.4362C19.8513 20.9787 23 16.8537 23 12C23 5.9225 18.0775 1 12 1Z"></path> </svg> </a> <div class="flex-1 flex-order-2 text-right"> <a href="/login?return_to=https%3A%2F%2Fgithub.com%2Flibxsmm%2Flibxsmm" class="HeaderMenu-link HeaderMenu-button d-inline-flex d-lg-none flex-order-1 f5 no-underline border color-border-default rounded-2 px-2 py-1 color-fg-inherit js-prevent-focus-on-mobile-nav" data-hydro-click="{"event_type":"authentication.click","payload":{"location_in_page":"site header menu","repository_id":null,"auth_type":"SIGN_UP","originating_url":"https://github.com/libxsmm/libxsmm","user_id":null}}" data-hydro-click-hmac="2afa87ffe185238cace1362850d084913a530bb58ce539590f2da34d72cae566" data-analytics-event="{"category":"Marketing nav","action":"click to Sign in","label":"ref_page:Marketing;ref_cta:Sign in;ref_loc:Header"}" > Sign in </a> </div> </div> <div class="HeaderMenu js-header-menu height-fit position-lg-relative d-lg-flex flex-column flex-auto top-0"> <div class="HeaderMenu-wrapper d-flex flex-column flex-self-start flex-lg-row flex-auto rounded rounded-lg-0"> <nav class="HeaderMenu-nav" aria-label="Global"> <ul class="d-lg-flex list-style-none"> <li class="HeaderMenu-item position-relative flex-wrap flex-justify-between flex-items-center d-block d-lg-flex flex-lg-nowrap flex-lg-items-center js-details-container js-header-menu-item"> <button type="button" class="HeaderMenu-link border-0 width-full width-lg-auto px-0 px-lg-2 py-lg-2 no-wrap d-flex flex-items-center flex-justify-between js-details-target" aria-expanded="false"> Product <svg opacity="0.5" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-down 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data-view-component="true" class="octicon octicon-copilot color-fg-subtle mr-3"> <path d="M23.922 16.992c-.861 1.495-5.859 5.023-11.922 5.023-6.063 0-11.061-3.528-11.922-5.023A.641.641 0 0 1 0 16.736v-2.869a.841.841 0 0 1 .053-.22c.372-.935 1.347-2.292 2.605-2.656.167-.429.414-1.055.644-1.517a10.195 10.195 0 0 1-.052-1.086c0-1.331.282-2.499 1.132-3.368.397-.406.89-.717 1.474-.952 1.399-1.136 3.392-2.093 6.122-2.093 2.731 0 4.767.957 6.166 2.093.584.235 1.077.546 1.474.952.85.869 1.132 2.037 1.132 3.368 0 .368-.014.733-.052 1.086.23.462.477 1.088.644 1.517 1.258.364 2.233 1.721 2.605 2.656a.832.832 0 0 1 .053.22v2.869a.641.641 0 0 1-.078.256ZM12.172 11h-.344a4.323 4.323 0 0 1-.355.508C10.703 12.455 9.555 13 7.965 13c-1.725 0-2.989-.359-3.782-1.259a2.005 2.005 0 0 1-.085-.104L4 11.741v6.585c1.435.779 4.514 2.179 8 2.179 3.486 0 6.565-1.4 8-2.179v-6.585l-.098-.104s-.033.045-.085.104c-.793.9-2.057 1.259-3.782 1.259-1.59 0-2.738-.545-3.508-1.492a4.323 4.323 0 0 1-.355-.508h-.016.016Zm.641-2.935c.136 1.057.403 1.913.878 2.497.442.544 1.134.938 2.344.938 1.573 0 2.292-.337 2.657-.751.384-.435.558-1.15.558-2.361 0-1.14-.243-1.847-.705-2.319-.477-.488-1.319-.862-2.824-1.025-1.487-.161-2.192.138-2.533.529-.269.307-.437.808-.438 1.578v.021c0 .265.021.562.063.893Zm-1.626 0c.042-.331.063-.628.063-.894v-.02c-.001-.77-.169-1.271-.438-1.578-.341-.391-1.046-.69-2.533-.529-1.505.163-2.347.537-2.824 1.025-.462.472-.705 1.179-.705 2.319 0 1.211.175 1.926.558 2.361.365.414 1.084.751 2.657.751 1.21 0 1.902-.394 2.344-.938.475-.584.742-1.44.878-2.497Z"></path><path d="M14.5 14.25a1 1 0 0 1 1 1v2a1 1 0 0 1-2 0v-2a1 1 0 0 1 1-1Zm-5 0a1 1 0 0 1 1 1v2a1 1 0 0 1-2 0v-2a1 1 0 0 1 1-1Z"></path> </svg> <div> <div class="color-fg-default h4">GitHub Copilot</div> Write better code with AI </div> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description pb-lg-3" data-analytics-event="{"location":"navbar","action":"security","context":"product","tag":"link","label":"security_link_product_navbar"}" href="https://github.com/features/security"> <svg aria-hidden="true" height="24" viewBox="0 0 24 24" version="1.1" width="24" data-view-component="true" class="octicon octicon-shield-check color-fg-subtle mr-3"> <path d="M16.53 9.78a.75.75 0 0 0-1.06-1.06L11 13.19l-1.97-1.97a.75.75 0 0 0-1.06 1.06l2.5 2.5a.75.75 0 0 0 1.06 0l5-5Z"></path><path d="m12.54.637 8.25 2.675A1.75 1.75 0 0 1 22 4.976V10c0 6.19-3.771 10.704-9.401 12.83a1.704 1.704 0 0 1-1.198 0C5.77 20.705 2 16.19 2 10V4.976c0-.758.489-1.43 1.21-1.664L11.46.637a1.748 1.748 0 0 1 1.08 0Zm-.617 1.426-8.25 2.676a.249.249 0 0 0-.173.237V10c0 5.46 3.28 9.483 8.43 11.426a.199.199 0 0 0 .14 0C17.22 19.483 20.5 15.461 20.5 10V4.976a.25.25 0 0 0-.173-.237l-8.25-2.676a.253.253 0 0 0-.154 0Z"></path> </svg> <div> <div class="color-fg-default h4">Security</div> Find and fix vulnerabilities </div> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description pb-lg-3" data-analytics-event="{"location":"navbar","action":"actions","context":"product","tag":"link","label":"actions_link_product_navbar"}" href="https://github.com/features/actions"> <svg aria-hidden="true" height="24" viewBox="0 0 24 24" version="1.1" width="24" data-view-component="true" class="octicon octicon-workflow color-fg-subtle mr-3"> <path d="M1 3a2 2 0 0 1 2-2h6.5a2 2 0 0 1 2 2v6.5a2 2 0 0 1-2 2H7v4.063C7 16.355 7.644 17 8.438 17H12.5v-2.5a2 2 0 0 1 2-2H21a2 2 0 0 1 2 2V21a2 2 0 0 1-2 2h-6.5a2 2 0 0 1-2-2v-2.5H8.437A2.939 2.939 0 0 1 5.5 15.562V11.5H3a2 2 0 0 1-2-2Zm2-.5a.5.5 0 0 0-.5.5v6.5a.5.5 0 0 0 .5.5h6.5a.5.5 0 0 0 .5-.5V3a.5.5 0 0 0-.5-.5ZM14.5 14a.5.5 0 0 0-.5.5V21a.5.5 0 0 0 .5.5H21a.5.5 0 0 0 .5-.5v-6.5a.5.5 0 0 0-.5-.5Z"></path> </svg> <div> <div class="color-fg-default h4">Actions</div> Automate any 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0-.25-.25Z"></path><path d="M10 17.75a.75.75 0 0 1 .75-.75h6.5a.75.75 0 0 1 0 1.5h-6.5a.75.75 0 0 1-.75-.75Zm-4 0a.75.75 0 0 1 .75-.75h.5a.75.75 0 0 1 0 1.5h-.5a.75.75 0 0 1-.75-.75Z"></path> </svg> <div> <div class="color-fg-default h4">Codespaces</div> Instant dev environments </div> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description pb-lg-3" data-analytics-event="{"location":"navbar","action":"issues","context":"product","tag":"link","label":"issues_link_product_navbar"}" href="https://github.com/features/issues"> <svg aria-hidden="true" height="24" viewBox="0 0 24 24" version="1.1" width="24" data-view-component="true" class="octicon octicon-issue-opened color-fg-subtle mr-3"> <path d="M12 1c6.075 0 11 4.925 11 11s-4.925 11-11 11S1 18.075 1 12 5.925 1 12 1ZM2.5 12a9.5 9.5 0 0 0 9.5 9.5 9.5 9.5 0 0 0 9.5-9.5A9.5 9.5 0 0 0 12 2.5 9.5 9.5 0 0 0 2.5 12Zm9.5 2a2 2 0 1 1-.001-3.999A2 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1.75h-9.69l-3.573 3.573A1.458 1.458 0 0 1 5 21.043V18.5H3.25a1.75 1.75 0 0 1-1.75-1.75ZM3.25 4a.25.25 0 0 0-.25.25v12.5c0 .138.112.25.25.25h2.5a.75.75 0 0 1 .75.75v3.19l3.72-3.72a.749.749 0 0 1 .53-.22h10a.25.25 0 0 0 .25-.25V4.25a.25.25 0 0 0-.25-.25Z"></path> </svg> <div> <div class="color-fg-default h4">Code Review</div> Manage code changes </div> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description pb-lg-3" data-analytics-event="{"location":"navbar","action":"discussions","context":"product","tag":"link","label":"discussions_link_product_navbar"}" href="https://github.com/features/discussions"> <svg aria-hidden="true" height="24" viewBox="0 0 24 24" version="1.1" width="24" data-view-component="true" class="octicon octicon-comment-discussion color-fg-subtle mr-3"> <path d="M1.75 1h12.5c.966 0 1.75.784 1.75 1.75v9.5A1.75 1.75 0 0 1 14.25 14H8.061l-2.574 2.573A1.458 1.458 0 0 1 3 15.543V14H1.75A1.75 1.75 0 0 1 0 12.25v-9.5C0 1.784.784 1 1.75 1ZM1.5 2.75v9.5c0 .138.112.25.25.25h2a.75.75 0 0 1 .75.75v2.19l2.72-2.72a.749.749 0 0 1 .53-.22h6.5a.25.25 0 0 0 .25-.25v-9.5a.25.25 0 0 0-.25-.25H1.75a.25.25 0 0 0-.25.25Z"></path><path d="M22.5 8.75a.25.25 0 0 0-.25-.25h-3.5a.75.75 0 0 1 0-1.5h3.5c.966 0 1.75.784 1.75 1.75v9.5A1.75 1.75 0 0 1 22.25 20H21v1.543a1.457 1.457 0 0 1-2.487 1.03L15.939 20H10.75A1.75 1.75 0 0 1 9 18.25v-1.465a.75.75 0 0 1 1.5 0v1.465c0 .138.112.25.25.25h5.5a.75.75 0 0 1 .53.22l2.72 2.72v-2.19a.75.75 0 0 1 .75-.75h2a.25.25 0 0 0 .25-.25v-9.5Z"></path> </svg> <div> <div class="color-fg-default h4">Discussions</div> Collaborate outside of code </div> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description" data-analytics-event="{"location":"navbar","action":"code_search","context":"product","tag":"link","label":"code_search_link_product_navbar"}" href="https://github.com/features/code-search"> <svg aria-hidden="true" height="24" viewBox="0 0 24 24" version="1.1" width="24" data-view-component="true" class="octicon octicon-code-square color-fg-subtle mr-3"> <path d="M10.3 8.24a.75.75 0 0 1-.04 1.06L7.352 12l2.908 2.7a.75.75 0 1 1-1.02 1.1l-3.5-3.25a.75.75 0 0 1 0-1.1l3.5-3.25a.75.75 0 0 1 1.06.04Zm3.44 1.06a.75.75 0 1 1 1.02-1.1l3.5 3.25a.75.75 0 0 1 0 1.1l-3.5 3.25a.75.75 0 1 1-1.02-1.1l2.908-2.7-2.908-2.7Z"></path><path d="M2 3.75C2 2.784 2.784 2 3.75 2h16.5c.966 0 1.75.784 1.75 1.75v16.5A1.75 1.75 0 0 1 20.25 22H3.75A1.75 1.75 0 0 1 2 20.25Zm1.75-.25a.25.25 0 0 0-.25.25v16.5c0 .138.112.25.25.25h16.5a.25.25 0 0 0 .25-.25V3.75a.25.25 0 0 0-.25-.25Z"></path> </svg> <div> <div class="color-fg-default h4">Code Search</div> Find more, search less </div> </a></li> </ul> </div> </div> <div class="HeaderMenu-column px-lg-4"> <div class="border-bottom pb-3 pb-lg-0 border-lg-bottom-0 border-bottom-0"> <span class="d-block h4 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12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> </ul> </div> </div> </div> </li> <li class="HeaderMenu-item position-relative flex-wrap flex-justify-between flex-items-center d-block d-lg-flex flex-lg-nowrap flex-lg-items-center js-details-container js-header-menu-item"> <button type="button" class="HeaderMenu-link border-0 width-full width-lg-auto px-0 px-lg-2 py-lg-2 no-wrap d-flex flex-items-center flex-justify-between js-details-target" aria-expanded="false"> Solutions <svg opacity="0.5" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-down HeaderMenu-icon ml-1"> <path d="M12.78 5.22a.749.749 0 0 1 0 1.06l-4.25 4.25a.749.749 0 0 1-1.06 0L3.22 6.28a.749.749 0 1 1 1.06-1.06L8 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Link--secondary" data-analytics-event="{"location":"navbar","action":"view_all_industries","context":"solutions","tag":"link","label":"view_all_industries_link_solutions_navbar"}" href="/solutions/industry"> View all industries </a></li> </ul> </div> </div> <div class="HeaderMenu-trailing-link rounded-bottom-2 flex-shrink-0 mt-lg-4 px-lg-4 py-4 py-lg-3 f5 text-semibold"> <a href="/solutions"> View all solutions <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-right HeaderMenu-trailing-link-icon"> <path d="M6.22 3.22a.75.75 0 0 1 1.06 0l4.25 4.25a.75.75 0 0 1 0 1.06l-4.25 4.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042L9.94 8 6.22 4.28a.75.75 0 0 1 0-1.06Z"></path> </svg> </a> </div> </div> </li> <li class="HeaderMenu-item position-relative flex-wrap flex-justify-between flex-items-center d-block d-lg-flex flex-lg-nowrap flex-lg-items-center js-details-container js-header-menu-item"> <button type="button" class="HeaderMenu-link border-0 width-full width-lg-auto px-0 px-lg-2 py-lg-2 no-wrap d-flex flex-items-center flex-justify-between js-details-target" aria-expanded="false"> Resources <svg opacity="0.5" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-down HeaderMenu-icon ml-1"> <path d="M12.78 5.22a.749.749 0 0 1 0 1.06l-4.25 4.25a.749.749 0 0 1-1.06 0L3.22 6.28a.749.749 0 1 1 1.06-1.06L8 8.939l3.72-3.719a.749.749 0 0 1 1.06 0Z"></path> </svg> </button> <div class="HeaderMenu-dropdown dropdown-menu rounded m-0 p-0 pt-2 pt-lg-4 position-relative position-lg-absolute left-0 left-lg-n3 pb-2 pb-lg-4 d-lg-flex flex-wrap dropdown-menu-wide"> <div class="HeaderMenu-column px-lg-4 border-lg-right mb-4 mb-lg-0 pr-lg-7"> <div class="border-bottom pb-3 pb-lg-0 border-lg-bottom-0"> <span class="d-block h4 color-fg-default my-1" id="resources-topics-heading">Topics</span> <ul 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data-view-component="true" class="octicon octicon-link-external HeaderMenu-external-icon color-fg-subtle"> <path d="M3.75 2h3.5a.75.75 0 0 1 0 1.5h-3.5a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h8.5a.25.25 0 0 0 .25-.25v-3.5a.75.75 0 0 1 1.5 0v3.5A1.75 1.75 0 0 1 12.25 14h-8.5A1.75 1.75 0 0 1 2 12.25v-8.5C2 2.784 2.784 2 3.75 2Zm6.854-1h4.146a.25.25 0 0 1 .25.25v4.146a.25.25 0 0 1-.427.177L13.03 4.03 9.28 7.78a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042l3.75-3.75-1.543-1.543A.25.25 0 0 1 10.604 1Z"></path> </svg> </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"executive_insights","context":"resources","tag":"link","label":"executive_insights_link_resources_navbar"}" href="https://github.com/solutions/executive-insights"> Executive Insights </a></li> </ul> </div> </div> </div> </li> <li class="HeaderMenu-item position-relative flex-wrap flex-justify-between flex-items-center d-block d-lg-flex flex-lg-nowrap flex-lg-items-center js-details-container js-header-menu-item"> <button type="button" class="HeaderMenu-link border-0 width-full width-lg-auto px-0 px-lg-2 py-lg-2 no-wrap d-flex flex-items-center flex-justify-between js-details-target" aria-expanded="false"> Open Source <svg opacity="0.5" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-chevron-down HeaderMenu-icon ml-1"> <path d="M12.78 5.22a.749.749 0 0 1 0 1.06l-4.25 4.25a.749.749 0 0 1-1.06 0L3.22 6.28a.749.749 0 1 1 1.06-1.06L8 8.939l3.72-3.719a.749.749 0 0 1 1.06 0Z"></path> </svg> </button> <div class="HeaderMenu-dropdown dropdown-menu rounded m-0 p-0 pt-2 pt-lg-4 position-relative position-lg-absolute left-0 left-lg-n3 pb-2 pb-lg-4 px-lg-4"> <div class="HeaderMenu-column"> <div class="border-bottom pb-3 pb-lg-0 pb-lg-3 mb-3 mb-lg-0 mb-lg-3"> <ul class="list-style-none f5" > <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description" data-analytics-event="{"location":"navbar","action":"github_sponsors","context":"open_source","tag":"link","label":"github_sponsors_link_open_source_navbar"}" href="/sponsors"> <div> <div class="color-fg-default h4">GitHub Sponsors</div> Fund open source developers </div> </a></li> </ul> </div> <div class="border-bottom pb-3 pb-lg-0 pb-lg-3 mb-3 mb-lg-0 mb-lg-3"> <ul class="list-style-none f5" > <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary d-flex flex-items-center Link--has-description" data-analytics-event="{"location":"navbar","action":"the_readme_project","context":"open_source","tag":"link","label":"the_readme_project_link_open_source_navbar"}" href="https://github.com/readme"> <div> <div class="color-fg-default h4">The ReadME Project</div> GitHub community articles </div> </a></li> </ul> </div> <div class="border-bottom pb-3 pb-lg-0 border-bottom-0"> <span class="d-block h4 color-fg-default my-1" id="open-source-repositories-heading">Repositories</span> <ul class="list-style-none f5" aria-labelledby="open-source-repositories-heading"> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"topics","context":"open_source","tag":"link","label":"topics_link_open_source_navbar"}" href="https://github.com/topics"> Topics </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" data-analytics-event="{"location":"navbar","action":"trending","context":"open_source","tag":"link","label":"trending_link_open_source_navbar"}" href="https://github.com/trending"> Trending </a></li> <li> <a class="HeaderMenu-dropdown-link d-block no-underline position-relative py-2 Link--secondary" 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6.94l3.22-3.22a.749.749 0 0 1 1.275.326.749.749 0 0 1-.215.734L9.06 8l3.22 3.22a.749.749 0 0 1-.326 1.275.749.749 0 0 1-.734-.215L8 9.06l-3.22 3.22a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042L6.94 8 3.72 4.78a.75.75 0 0 1 0-1.06Z"></path> </svg></button> </div> </div> </div> <scrollable-region data-labelled-by="custom-scopes-dialog-title"> <div data-view-component="true" class="Overlay-body"> <div data-target="custom-scopes.customScopesModalDialogFlash"></div> <div hidden class="create-custom-scope-form" data-target="custom-scopes.createCustomScopeForm"> <!-- '"` --><!-- </textarea></xmp> --></option></form><form id="custom-scopes-dialog-form" data-turbo="false" action="/search/custom_scopes" accept-charset="UTF-8" method="post"><input type="hidden" data-csrf="true" name="authenticity_token" value="R/wKdyNZPDxv+cfuSPX0n+iJVbaMq0GPOwMdv7awrZ44P6jWrvaZaDBN5ZRvtecjiuQzGbsBoecHIiP3KiTFRA==" /> <div data-target="custom-scopes.customScopesModalDialogFlash"></div> <input type="hidden" 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src=\"https://camo.githubusercontent.com/8b3ecad194f11320fdeace777c3e79c46ec06c6755553cdb22527c8745019614/68747470733a2f2f7363616e2e636f7665726974792e636f6d2f70726f6a656374732f373430352f62616467652e737667\" alt=\"Static Analysis Status\" title=\"Static Analysis Status\" data-canonical-src=\"https://scan.coverity.com/projects/7405/badge.svg\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e \u003ca href=\"https://libxsmm.readthedocs.io/\" rel=\"nofollow\"\u003e\u003cimg src=\"https://camo.githubusercontent.com/2bb59a49fb2b2cf62074495331376db0469d09c5b3c1c9d66ec527cf12ae2e2f/68747470733a2f2f72656164746865646f63732e6f72672f70726f6a656374732f6c696278736d6d2f62616467652f3f76657273696f6e3d6c6174657374\" alt=\"Read the Docs\" title=\"Read the Docs\" data-canonical-src=\"https://readthedocs.org/projects/libxsmm/badge/?version=latest\" style=\"max-width: 100%;\"\u003e\u003c/a\u003e\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eLIBXSMM is a library for specialized dense and sparse matrix operations as well as for deep learning primitives such as small convolutions. The library is targeting Intel Architecture with \u003cspan\u003eIntel SSE\u003c/span\u003e, \u003cspan\u003eIntel AVX\u003c/span\u003e, \u003cspan\u003eIntel AVX2\u003c/span\u003e, \u003cspan\u003eIntel AVX‑512\u003c/span\u003e (with VNNI and Bfloat16), and \u003cspan\u003eIntel AMX\u003c/span\u003e (Advanced Matrix Extensions) supported by future Intel processor code-named Sapphire Rapids. Code generation is mainly based on \u003cspan\u003eJust‑In‑Time (JIT)\u003c/span\u003e code specialization for compiler-independent performance (matrix multiplications, matrix transpose/copy, sparse functionality, and deep learning). LIBXSMM is suitable for \"build once and deploy everywhere\", i.e., no special target flags are needed to exploit the available performance. Supported GEMM datatypes are: \u003ccode\u003eFP64\u003c/code\u003e, \u003ccode\u003eFP32\u003c/code\u003e, \u003ccode\u003ebfloat16\u003c/code\u003e, \u003ccode\u003eint16\u003c/code\u003e, and \u003ccode\u003eint8\u003c/code\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eFor a list questions and answers, please also have a look at \u003ca href=\"https://github.com/libxsmm/libxsmm/wiki/Q\u0026amp;A\"\u003ehttps://github.com/libxsmm/libxsmm/wiki/Q\u0026amp;A\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eWhere to go for documentation?\u003c/strong\u003e\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003cstrong\u003eReadtheDocs\u003c/strong\u003e: \u003ca href=\"https://libxsmm.readthedocs.io/\" rel=\"nofollow\"\u003emain\u003c/a\u003e and \u003ca href=\"https://libxsmm.readthedocs.io/libxsmm_samples/\" rel=\"nofollow\"\u003esample\u003c/a\u003e documentation with full text search.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003ePDF\u003c/strong\u003e: \u003ca href=\"https://github.com/libxsmm/libxsmm/raw/main/documentation/libxsmm.pdf\"\u003emain\u003c/a\u003e documentation file, and separate \u003ca href=\"https://github.com/libxsmm/libxsmm/raw/main/documentation/libxsmm_samples.pdf\"\u003esample\u003c/a\u003e documentation.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eArticles\u003c/strong\u003e: \u003ca href=\"https://software.intel.com/sites/default/files/parallel-universe-issue-34.pdf\" rel=\"nofollow\"\u003emagazine article\u003c/a\u003e incl. \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/samples/magazine\"\u003esample code\u003c/a\u003e (full list of \u003ca href=\"#articles\"\u003eArticles\u003c/a\u003e).\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-getting-started\"\u003e\u003c/a\u003e\u003ca name=\"user-content-hello-libxsmm\"\u003e\u003c/a\u003e\u003cstrong\u003eGetting Started\u003c/strong\u003e: The following C++ code is focused on a specific functionality but may be considered as \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/samples/hello\"\u003eHello LIBXSMM\u003c/a\u003e. Build the example with \u003ccode\u003ecd /path/to/libxsmm; make STATIC=0\u003c/code\u003e (shared library), save the code under \u003ccode\u003ehello.cpp\u003c/code\u003e (below) and compile with \u003ccode\u003eg++ -I/path/to/libxsmm/include hello.cpp -L/path/to/libxsmm/lib -lxsmm -lblas -o hello\u003c/code\u003e (GNU CCC), and finally execute with \u003ccode\u003eLD_LIBRARY_PATH=/path/to/libxsmm/lib LIBXSMM_VERBOSE=2 ./hello\u003c/code\u003e.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-c++ notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"#include \u0026lt;libxsmm.h\u0026gt;\n#include \u0026lt;vector\u0026gt;\nint main(int argc, char* argv[]) {\n typedef double T;\n int batchsize = 1000, m = 13, n = 5, k = 7;\n std::vector\u0026lt;T\u0026gt; a(batchsize * m * k), b(batchsize * k * n), c(m * n, 0);\n /* C/C++ and Fortran interfaces are available */\n typedef libxsmm_mmfunction\u0026lt;T\u0026gt; kernel_type;\n /* generates and dispatches a matrix multiplication kernel (C++ functor) */\n kernel_type kernel(LIBXSMM_GEMM_FLAG_NONE, m, n, k, 1.0 /*alpha*/, 1.0 /*beta*/);\n assert(kernel);\n for (int i = 0; i \u0026lt; batchsize; ++i) { /* initialize input */\n for (int ki = 0; ki \u0026lt; k; ++ki) {\n for (int j = 0; j \u0026lt; m; ++j) a[i * j * ki] = static_cast\u0026lt;T\u0026gt;(1) / ((i + j + ki) % 25);\n for (int j = 0; j \u0026lt; n; ++j) b[i * j * ki] = static_cast\u0026lt;T\u0026gt;(7) / ((i + j + ki) % 75);\n }\n }\n /* kernel multiplies and accumulates matrices: C += Ai * Bi */\n for (int i = 0; i \u0026lt; batchsize; ++i) kernel(\u0026amp;a[i * m * k], \u0026amp;b[i * k * n], \u0026amp;c[0]);\n}\"\u003e\u003cpre\u003e#\u003cspan class=\"pl-k\"\u003einclude\u003c/span\u003e \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\u0026lt;\u003c/span\u003elibxsmm.h\u003cspan class=\"pl-pds\"\u003e\u0026gt;\u003c/span\u003e\u003c/span\u003e\n#\u003cspan class=\"pl-k\"\u003einclude\u003c/span\u003e \u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\u0026lt;\u003c/span\u003evector\u003cspan class=\"pl-pds\"\u003e\u0026gt;\u003c/span\u003e\u003c/span\u003e\n\u003cspan class=\"pl-k\"\u003eint\u003c/span\u003e \u003cspan class=\"pl-en\"\u003emain\u003c/span\u003e(\u003cspan class=\"pl-k\"\u003eint\u003c/span\u003e argc, \u003cspan class=\"pl-k\"\u003echar\u003c/span\u003e* argv[]) {\n \u003cspan class=\"pl-k\"\u003etypedef\u003c/span\u003e \u003cspan class=\"pl-k\"\u003edouble\u003c/span\u003e T;\n \u003cspan class=\"pl-k\"\u003eint\u003c/span\u003e batchsize = \u003cspan class=\"pl-c1\"\u003e1000\u003c/span\u003e, m = \u003cspan class=\"pl-c1\"\u003e13\u003c/span\u003e, n = \u003cspan class=\"pl-c1\"\u003e5\u003c/span\u003e, k = \u003cspan class=\"pl-c1\"\u003e7\u003c/span\u003e;\n std::vector\u0026lt;T\u0026gt; \u003cspan class=\"pl-c1\"\u003ea\u003c/span\u003e(batchsize * m * k), \u003cspan class=\"pl-c1\"\u003eb\u003c/span\u003e(batchsize * k * n), \u003cspan class=\"pl-c1\"\u003ec\u003c/span\u003e(m * n, \u003cspan class=\"pl-c1\"\u003e0\u003c/span\u003e);\n \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e/*\u003c/span\u003e C/C++ and Fortran interfaces are available \u003cspan class=\"pl-c\"\u003e*/\u003c/span\u003e\u003c/span\u003e\n \u003cspan class=\"pl-k\"\u003etypedef\u003c/span\u003e libxsmm_mmfunction\u0026lt;T\u0026gt; kernel_type;\n \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e/*\u003c/span\u003e generates and dispatches a matrix multiplication kernel (C++ functor) \u003cspan class=\"pl-c\"\u003e*/\u003c/span\u003e\u003c/span\u003e\n kernel_type \u003cspan class=\"pl-smi\"\u003ekernel\u003c/span\u003e(LIBXSMM_GEMM_FLAG_NONE, m, n, k, \u003cspan class=\"pl-c1\"\u003e1.0\u003c/span\u003e \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e/*\u003c/span\u003ealpha\u003cspan class=\"pl-c\"\u003e*/\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"pl-c1\"\u003e1.0\u003c/span\u003e \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e/*\u003c/span\u003ebeta\u003cspan class=\"pl-c\"\u003e*/\u003c/span\u003e\u003c/span\u003e);\n \u003cspan class=\"pl-c1\"\u003eassert\u003c/span\u003e(kernel);\n \u003cspan class=\"pl-k\"\u003efor\u003c/span\u003e (\u003cspan class=\"pl-k\"\u003eint\u003c/span\u003e i = \u003cspan class=\"pl-c1\"\u003e0\u003c/span\u003e; i \u0026lt; batchsize; ++i) { \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e/*\u003c/span\u003e initialize input \u003cspan class=\"pl-c\"\u003e*/\u003c/span\u003e\u003c/span\u003e\n \u003cspan class=\"pl-k\"\u003efor\u003c/span\u003e (\u003cspan class=\"pl-k\"\u003eint\u003c/span\u003e ki = \u003cspan class=\"pl-c1\"\u003e0\u003c/span\u003e; ki \u0026lt; k; ++ki) {\n \u003cspan class=\"pl-k\"\u003efor\u003c/span\u003e (\u003cspan class=\"pl-k\"\u003eint\u003c/span\u003e j = \u003cspan class=\"pl-c1\"\u003e0\u003c/span\u003e; j \u0026lt; m; ++j) a[i * j * ki] = \u003cspan class=\"pl-k\"\u003estatic_cast\u003c/span\u003e\u0026lt;T\u0026gt;(\u003cspan class=\"pl-c1\"\u003e1\u003c/span\u003e) / ((i + j + ki) % \u003cspan class=\"pl-c1\"\u003e25\u003c/span\u003e);\n \u003cspan class=\"pl-k\"\u003efor\u003c/span\u003e (\u003cspan class=\"pl-k\"\u003eint\u003c/span\u003e j = \u003cspan class=\"pl-c1\"\u003e0\u003c/span\u003e; j \u0026lt; n; ++j) b[i * j * ki] = \u003cspan class=\"pl-k\"\u003estatic_cast\u003c/span\u003e\u0026lt;T\u0026gt;(\u003cspan class=\"pl-c1\"\u003e7\u003c/span\u003e) / ((i + j + ki) % \u003cspan class=\"pl-c1\"\u003e75\u003c/span\u003e);\n }\n }\n \u003cspan class=\"pl-c\"\u003e\u003cspan class=\"pl-c\"\u003e/*\u003c/span\u003e kernel multiplies and accumulates matrices: C += Ai * Bi \u003cspan class=\"pl-c\"\u003e*/\u003c/span\u003e\u003c/span\u003e\n \u003cspan class=\"pl-k\"\u003efor\u003c/span\u003e (\u003cspan class=\"pl-k\"\u003eint\u003c/span\u003e i = \u003cspan class=\"pl-c1\"\u003e0\u003c/span\u003e; i \u0026lt; batchsize; ++i) \u003cspan class=\"pl-c1\"\u003ekernel\u003c/span\u003e(\u0026amp;a[i * m * k], \u0026amp;b[i * k * n], \u0026amp;c[\u003cspan class=\"pl-c1\"\u003e0\u003c/span\u003e]);\n}\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003ePlain \u003ca href=\"https://github.com/libxsmm/libxsmm/blob/main/samples/hello/hello.c\"\u003eC code\u003c/a\u003e as well as \u003ca href=\"https://github.com/libxsmm/libxsmm/blob/main/samples/hello/hello.f\"\u003eFortran code\u003c/a\u003e resemble the same \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/samples/hello\"\u003eexample\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-what-is-a-small-matrix-multiplication\"\u003e\u003c/a\u003e\u003cstrong\u003eWhat is a small matrix multiplication?\u003c/strong\u003e When characterizing the problem-size by using the M, N, and K parameters, a problem-size suitable for LIBXSMM falls approximately within \u003ci\u003e(M N K)\u003csup\u003e1/3\u003c/sup\u003e \u0026lt;= 64\u003c/i\u003e (which illustrates that non-square matrices or even \"tall and skinny\" shapes are covered as well). The library is typically used to generate code up to the specified \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_tune.md#auto-dispatch\"\u003ethreshold\u003c/a\u003e. Raising the threshold may not only generate excessive amounts of code (due to unrolling in M or K dimension), but also miss to implement a tiling scheme to effectively utilize the cache hierarchy. For auto-dispatched problem-sizes above the configurable threshold (explicitly JIT'ted code is \u003cstrong\u003enot\u003c/strong\u003e subject to the threshold), LIBXSMM is falling back to BLAS. In terms of GEMM, the supported kernels are limited to \u003cem\u003eAlpha := 1\u003c/em\u003e, \u003cem\u003eBeta := { 1, 0 }\u003c/em\u003e, and \u003cem\u003eTransA := 'N'\u003c/em\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-what-is-a-small-convolution\"\u003e\u003c/a\u003e\u003cstrong\u003eWhat is a small convolution?\u003c/strong\u003e In the last years, new workloads such as deep learning and more specifically convolutional neural networks (CNN) emerged and are pushing the limits of today's hardware. One of the expensive kernels is a small convolution with certain kernel sizes such that calculations in the frequency space is not the most efficient method when compared with direct convolutions. LIBXSMM's current support for convolutions aims for an easy-to-use invocation of small (direct) convolutions, which are intended for CNN training and classification.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eInterfaces and Domains\u003ca name=\"user-content-interfaces\"\u003e\u003c/a\u003e\u003c/h2\u003e\u003ca id=\"user-content-interfaces-and-domains\" class=\"anchor\" aria-label=\"Permalink: Interfaces and Domains\" href=\"#interfaces-and-domains\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eOverview\u003ca name=\"user-content-general-interface\"\u003e\u003c/a\u003e\u003c/h3\u003e\u003ca id=\"user-content-overview\" class=\"anchor\" aria-label=\"Permalink: Overview\" href=\"#overview\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003ePlease have a look at \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/include\"\u003ehttps://github.com/libxsmm/libxsmm/tree/main/include\u003c/a\u003e for all published functions. Get started with the following list of available domains and documented functionality:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eMM: \u003ca href=\"#matrix-multiplication\"\u003eMatrix Multiplication\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eTPP: \u003ca href=\"/libxsmm/libxsmm/blob/main/libxsmm_tpp.md\"\u003eTensor Processing Primitives\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eDNN: \u003ca href=\"#deep-neural-networks\"\u003eDeep Neural Networks\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eAUX: \u003ca href=\"#service-functions\"\u003eService Functions\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003ePERF: \u003ca href=\"#performance\"\u003ePerformance\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eBE: \u003ca href=\"#jit-backend\"\u003eBackend\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003eTo initialize library internal resources, an explicit initialization routine helps to avoid lazy initialization overhead when calling LIBXSMM for the first time. The library deallocates internal resources at program exit, but also provides a companion of the afore mentioned initialization (finalize).\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-c notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"/** Initialize the library; pay for setup cost at a specific point. */\nvoid libxsmm_init(void);\n/** De-initialize the library and free internal memory (optional). */\nvoid libxsmm_finalize(void);\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c\"\u003e/** Initialize the library; pay for setup cost at a specific point. */\u003c/span\u003e\n\u003cspan class=\"pl-smi\"\u003evoid\u003c/span\u003e \u003cspan class=\"pl-en\"\u003elibxsmm_init\u003c/span\u003e(\u003cspan class=\"pl-smi\"\u003evoid\u003c/span\u003e);\n\u003cspan class=\"pl-c\"\u003e/** De-initialize the library and free internal memory (optional). */\u003c/span\u003e\n\u003cspan class=\"pl-smi\"\u003evoid\u003c/span\u003e \u003cspan class=\"pl-en\"\u003elibxsmm_finalize\u003c/span\u003e(\u003cspan class=\"pl-smi\"\u003evoid\u003c/span\u003e);\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eMatrix Multiplication\u003ca name=\"user-content-interface-for-matrix-multiplication\"\u003e\u003c/a\u003e\u003c/h3\u003e\u003ca id=\"user-content-matrix-multiplication\" class=\"anchor\" aria-label=\"Permalink: Matrix Multiplication\" href=\"#matrix-multiplication\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThis domain (MM) supports Small Matrix Multiplications (SMM), batches of multiple multiplications as well as the industry-standard interface for GEneral Matrix Matrix multiplication (GEMM).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThe \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md\"\u003eMatrix Multiplication domain (MM)\u003c/a\u003e contains routines for:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#overview\"\u003eSmall, tiled, and parallelized matrix multiplications\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#manual-code-dispatch\"\u003eManual code dispatch (customized matrix batches)\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#batched-multiplication\"\u003eBatched multiplication (explicit interface)\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#call-wrapper\"\u003eCall wrapper (static and dynamic linkage)\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eDeep Learning\u003ca name=\"user-content-interface-for-dl\"\u003e\u003c/a\u003e\u003c/h3\u003e\u003ca id=\"user-content-deep-learning\" class=\"anchor\" aria-label=\"Permalink: Deep Learning\" href=\"#deep-learning\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe Deep Learning domain is detailed by the following \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/samples/deeplearning\"\u003esample codes\u003c/a\u003e. Here we demonstrate how common operators in deep learning applications (GEMM with activation function fusion, Convolutions with activation function fusion, various norming operators, and pooling operators, etc.) can be implemented using the Tensor Processing Primitive provided by LIBXSMM. Example drivers for performance evaluation are provided as part of \u003ca href=\"https://github.com/libxsmm/libxsmm-dnn/tree/main/tests\"\u003eLIBXSMM_DNN\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eService Functions\u003c/h3\u003e\u003ca id=\"user-content-service-functions\" class=\"anchor\" aria-label=\"Permalink: Service Functions\" href=\"#service-functions\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eFor convenient operation of the library and to ease integration, some service routines are available. These routines may not belong to the core functionality of LIBXSMM (SMM or DNN domain), but users are encouraged to use this domain (AUX). There are two categories: \u003cspan\u003e(1) routines\u003c/span\u003e which are available for C and FORTRAN, and \u003cspan\u003e(2) routines\u003c/span\u003e that are only available per C interface.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThe \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md\"\u003eservice function domain (AUX)\u003c/a\u003e contains routines for:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#getting-and-setting-the-target-architecture\"\u003eGetting and setting the target architecture\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#getting-and-setting-the-verbosity\"\u003eGetting and setting the verbosity\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#timer-facility\"\u003eMeasuring time durations (timer)\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#user-data-dispatch\"\u003eDispatching user-data and multiple kernels\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#meta-image-file-io\"\u003eLoading and storing data (I/O)\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#memory-allocation\"\u003eAllocating memory\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eBackend\u003ca name=\"user-content-jit-backend\"\u003e\u003c/a\u003e\u003c/h3\u003e\u003ca id=\"user-content-backend\" class=\"anchor\" aria-label=\"Permalink: Backend\" href=\"#backend\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eMore information about the JIT-backend and the code generator can be found in a separate \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_be.md\"\u003edocument\u003c/a\u003e. The \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/samples/encoder\"\u003eencoder sample collection\u003c/a\u003e can help to get started writing a kernel using LIBXSMM. Please note, LIBXSMM's stand-alone \u003ca name=\"user-content-generator-driver\"\u003e\u003c/a\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_be.md#generator-driver\"\u003egenerator-driver\u003c/a\u003e is considered legacy (deprecated).\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eBuild Instructions\u003c/h2\u003e\u003ca id=\"user-content-build-instructions\" class=\"anchor\" aria-label=\"Permalink: Build Instructions\" href=\"#build-instructions\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eOverview\u003c/h3\u003e\u003ca id=\"user-content-overview-1\" class=\"anchor\" aria-label=\"Permalink: Overview\" href=\"#overview-1\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe main interface file is \u003cem\u003egenerated\u003c/em\u003e, and it is therefore \u003cstrong\u003enot\u003c/strong\u003e stored in the code repository. To inspect the interface for \u003ca href=\"https://github.com/libxsmm/libxsmm/blob/main/src/template/libxsmm.h\"\u003eC/C++\u003c/a\u003e and \u003ca href=\"https://github.com/libxsmm/libxsmm/blob/main/src/template/libxsmm.f\"\u003eFORTRAN\u003c/a\u003e, one can take a look at the template files used to generate the actual interface. There are two general ways to build and use LIBXSMM:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"#classic-library-abi\"\u003eClassic Library (ABI)\u003c/a\u003e and \u003ca href=\"#link-instructions\"\u003eLink Instructions\u003c/a\u003e (C/C++ and FORTRAN)\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"#header-only\"\u003eHeader-Only\u003c/a\u003e (C and C++)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: LIBXSMM is available as prebuilt package for Fedora/RedHat/CentOS, Debian/Ubuntu, FreeBSD, and others. Further, LIBXSMM can be installed with the \u003ca href=\"https://computing.llnl.gov/projects/spack-hpc-package-manager\" rel=\"nofollow\"\u003eSpack Package Manager\u003c/a\u003e or per \u003ca href=\"https://github.com/easybuilders\"\u003eEasyBuild+EasyConfig\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eClassic Library (ABI)\u003c/h3\u003e\u003ca id=\"user-content-classic-library-abi\" class=\"anchor\" aria-label=\"Permalink: Classic Library (ABI)\" href=\"#classic-library-abi\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThere are two ways to rely on prebuilt code for a given project: \u003cspan\u003e(1) using\u003c/span\u003e LIBXSMM's Makefile based build system, \u003cspan\u003e(2) or\u003c/span\u003e using another build system and writing own \u003ca href=\"#rules-for-building-libxsmm\"\u003erules for building LIBXSMM\u003c/a\u003e. The Makefile based build system relies on \u003cspan\u003eGNU Make\u003c/span\u003e (typically associated with the \u003ccode\u003emake\u003c/code\u003e command, but e.g. FreeBSD is calling it \u003ccode\u003egmake\u003c/code\u003e). The build can be customized by using \u003cspan\u003ekey‑value\u003c/span\u003e pairs. \u003cspan\u003eKey‑value\u003c/span\u003e pairs can be supplied in two ways: \u003cspan\u003e(1) after\u003c/span\u003e the \"make\" command, or \u003cspan\u003e(2) prior\u003c/span\u003e to the \"make\" command (\u003ccode\u003eenv\u003c/code\u003e) which is effectively the same as exporting the \u003cspan\u003ekey‑value\u003c/span\u003e pair as an environment variable (\u003ccode\u003eexport\u003c/code\u003e, or \u003ccode\u003esetenv\u003c/code\u003e). Both methods can be mixed (the second method may require make's \u003ccode\u003e-e\u003c/code\u003e flag).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-zero-config-abi\"\u003e\u003c/a\u003eIn contrast to \u003ca href=\"#zero-config\"\u003eheader-only\u003c/a\u003e which does not require configuration by default, 3rd-party build systems can compile and link LIBXSMM's sources but still avoid configuring the library (per \u003ccode\u003elibxsmm_config.py\u003c/code\u003e). The prerequisite to omit configuration is to opt-in by defining LIBXSMM_DEFAULT_CONFIG (\u003ccode\u003e-D\u003c/code\u003e). The zero-config feature is not available for LIBXSMM's Fortran interface.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: By default, C/C++ and FORTRAN compilers are needed (some sample code is written in C++). Beside of specifying the compilers (\u003ccode\u003emake CXX=g++ CC=gcc FC=gfortran\u003c/code\u003e and maybe \u003ccode\u003eAR=ar\u003c/code\u003e), the need for a FORTRAN compiler can be relaxed (\u003ccode\u003emake FC=\u003c/code\u003e or \u003ccode\u003emake FORTRAN=0\u003c/code\u003e). The latter affects the availability of the MODule file and the corresponding \u003ccode\u003elibxsmm.f\u003c/code\u003e library (the interface \u003ccode\u003elibxsmm.f\u003c/code\u003e is still generated).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThe build system considers a set of given key-value pairs as a single unique build and triggers a rebuild for a distinct set of flags. For more advanced builds or additional background, please consult the section about \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_tune.md\"\u003eCustomization\u003c/a\u003e. To generate the interface of the library inside of the \u003ccode\u003einclude\u003c/code\u003e directory and to build the static library (by default, STATIC=1 is activated). Run any (or both) of the following command(s):\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make STATIC=0\nmake\"\u003e\u003cpre\u003emake STATIC=0\nmake\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eOn CRAY systems, the CRAY Compiling Environment (CCE) should be used regardless of utilizing the CRAY compiler, the Intel Compiler, or the \u003cspan\u003eGNU Compiler Collection (GCC)\u003c/span\u003e. The CCE is eventually suppressing to build shared libraries (STATIC=0). In any case, \u003cspan\u003e(1) switch\u003c/span\u003e to the desired compiler (module load/switch), and \u003cspan\u003e(2) rely\u003c/span\u003e on:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make CXX=CC CC=cc FC=ftn\"\u003e\u003cpre\u003emake CXX=CC CC=cc FC=ftn\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eA variety of build environments is out-of-the-box compatible, see \u003ca href=\"https://github.com/libxsmm/libxsmm/wiki/Compatibility\"\u003ehttps://github.com/libxsmm/libxsmm/wiki/Compatibility\u003c/a\u003e. If the build process is not successful, it may help to avoid advanced GCC flags. This is useful with a tool chain, which pretends to be GCC-compatible (and is treated as such) but fails to consume the afore mentioned flags:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make COMPATIBLE=1\"\u003e\u003cpre\u003emake COMPATIBLE=1\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-outdated-binutils\"\u003e\u003c/a\u003eIn case of outdated Binutils, compilation can fail to assemble code when building the library (this has nothing to do with JIT-generated code and it does not affect how JIT-code is targeting the system). LIBXSMM implements some functionality using compiler-intrinsics and multiple code-paths which are scheduled according to CPUID. In contrast to \u003ccode\u003eINTRINSICS=2\u003c/code\u003e (default), \u003ccode\u003eINTRINSICS=1\u003c/code\u003e enables a fully static code path according to the desired target. If no target is given (e.g., \u003ccode\u003eAVX=3\u003c/code\u003e, or \u003ccode\u003eAVX=2\u003c/code\u003e), instruction set extensions cannot be leveraged for such code-paths. Try to fix failing compilation by building the latest GNU Binutils (and \u003ccode\u003eexport PATH=/path/to/binutils/bin:${PATH}\u003c/code\u003e). Binutils are versioned independently of \u003cspan\u003eGNU GCC\u003c/span\u003e and other compilers. If one cannot update Binutils, work around with a CPUID-value as tabulated in \u003ca href=\"https://github.com/libxsmm/libxsmm/blob/main/include/libxsmm_cpuid.h\"\u003elibxsmm_cpuid.h\u003c/a\u003e: start at the upper end (less than 1999) and decrement until compilation passes (make INTRINSICS=\u003cem\u003eCPUID\u003c/em\u003e, e.g., \u003ccode\u003emake INTRINSICS=1021\u003c/code\u003e). As a last resort, rely on a fully static code path:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make INTRINSICS=1\"\u003e\u003cpre\u003emake INTRINSICS=1\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eTo test and validate a build, please consult \u003ca href=\"https://github.com/libxsmm/libxsmm/wiki/Validation\"\u003ehttps://github.com/libxsmm/libxsmm/wiki/Validation\u003c/a\u003e. To run some basic sanity checks, remember that each set of given key-value pairs represents a different build (and test):\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make STATIC=0 tests\"\u003e\u003cpre\u003emake STATIC=0 tests\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eTo remove intermediate files, or to remove all generated files and folders (including the interface and the library archives), run one of the make-targets below. An additional distclean-target recursively cleans the entire tree (after \u003cspan\u003eversion 1.9\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make clean\nmake realclean\"\u003e\u003cpre\u003emake clean\nmake realclean\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-fortran\"\u003e\u003c/a\u003eFORTRAN code can make use of LIBXSMM:\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003eBy using the module and linking with \u003ccode\u003elibxsmmf\u003c/code\u003e, \u003ccode\u003elibxsmm\u003c/code\u003e, and \u003ccode\u003elibxsmmext\u003c/code\u003e,\u003c/li\u003e\n\u003cli\u003e\u003ca name=\"user-content-header-only-fortran\"\u003e\u003c/a\u003eBy including \u003ccode\u003elibxsmm.f\u003c/code\u003e and linking with \u003ccode\u003elibxsmm\u003c/code\u003e, and \u003ccode\u003elibxsmmext\u003c/code\u003e, or\u003c/li\u003e\n\u003cli\u003eBy (implicitly) calling a SUBROUTINE and linking with \u003ccode\u003elibxsmm\u003c/code\u003e, and \u003ccode\u003elibxsmmext\u003c/code\u003e.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: \u003ccode\u003elibxsmmf\u003c/code\u003e requires \u003ccode\u003elibxsmmext\u003c/code\u003e (starting with LIBXSMM 2.0), and thereby requires to link with the OpenMP runtime as well.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eUsing the Fortran module (or including the interface), requires at least a \u003cspan\u003eFortran 2003\u003c/span\u003e compiler (F2K3). \u003cspan\u003eFORTRAN 77\u003c/span\u003e compatibility is only implicitly available (no interface), and the available subset of routines is documented in \u003ccode\u003elibxsmm.f\u003c/code\u003e and marked with \u003ca href=\"https://github.com/libxsmm/libxsmm/search?q=implementation+provided+for+Fortran+77+compatibility\"\u003ecomments\u003c/a\u003e (part of the implementation).\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eHeader-Only\u003c/h3\u003e\u003ca id=\"user-content-header-only\" class=\"anchor\" aria-label=\"Permalink: Header-Only\" href=\"#header-only\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cspan\u003eVersion 1.4.4\u003c/span\u003e introduced support for \"header-only\" usage in C and C++. By only including \u003ccode\u003elibxsmm_source.h\u003c/code\u003e allows to get around building the library. However, this gives up on a clearly defined application binary interface (ABI). An ABI may allow for hot-fixes after deploying an application (when relying on the shared library form), and it may also ensure to only rely on the public interface of LIBXSMM. In contrast, the header-only form not only exposes the internal implementation of LIBXSMM but can also increase the turnaround time during development of an application (due to longer compilation times). The header file is intentionally named \"libxsmm_\u003cstrong\u003esource\u003c/strong\u003e.h\" since this header file relies on the \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/src\"\u003esrc\u003c/a\u003e directory (with the implications as noted earlier).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-zero-config\"\u003e\u003c/a\u003eThe header-only form depends on \u003ccode\u003elibxsmm_source.h\u003c/code\u003e which is \u003cem\u003egenerated\u003c/em\u003e according to the content of the source folder (\u003ccode\u003esrc\u003c/code\u003e). \u003cspan\u003eLIBXSMM 1.16\u003c/span\u003e (and later) provides header-only support without invoking a make-target (zero configuration) for any given checkout of LIBXSMM. To use configured header-only (non-default), LIBXSMM_CONFIGURED must be defined (\u003ccode\u003e-D\u003c/code\u003e). Previously, it was necessary to invoke \u003ccode\u003emake header-only\u003c/code\u003e (v1.6.2 or later), \u003ccode\u003emake cheader\u003c/code\u003e (prior to v1.6.2), or any target building the library (\u003ccode\u003emake\u003c/code\u003e). The zero-config feature allows 3rd-party build systems an easier integration of LIBXSMM, which also holds true if the system builds LIBXSMM from source (see \u003ca href=\"#zero-config-abi\"\u003eclassic ABI\u003c/a\u003e). Fortran code may \u003ca href=\"#header-only-fortran\"\u003einclude\u003c/a\u003e \u003ccode\u003elibxsmm.f\u003c/code\u003e but still requires that interface to be generated.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: building an application applies the same build settings to LIBXSMM! For instance, to omit debug code inside of LIBXSMM \u003ccode\u003eNDEBUG\u003c/code\u003e must be defined (\u003ccode\u003e-DNDEBUG\u003c/code\u003e).\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eRules for building LIBXSMM\u003c/h2\u003e\u003ca id=\"user-content-rules-for-building-libxsmm\" class=\"anchor\" aria-label=\"Permalink: Rules for building LIBXSMM\" href=\"#rules-for-building-libxsmm\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eLIBXSMM can be used as header-only library, i.e., no source code must be (pre-)built. However, it can be desirable to build LIBXSMM as an intermediate library using a custom setup or build system. The latter can still implement custom build rules to configure LIBXSMM's interface before building the code. More likely, building LIBXSMM from source in a custom fashion can still be omitting to configure the interface and rely on \"(zero-config)[#zero-config-abi]\", i.e., defining LIBXSMM_DEFAULT_CONFIG (\u003ccode\u003e-DLIBXSMM_DEFAULT_CONFIG\u003c/code\u003e). For example, a CMake module for LIBXSMM can look like:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-cmake notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"include(FetchContent)\nFetchContent_Declare(\n xsmm\n URL https://github.com/chelini/libxsmm/archive/\u0026lt;your-preferred-revision\u0026gt;.tar.gz\n URL_HASH SHA256=\u0026lt;sha256sum-corresponding-to-above-revision\u0026gt;\n)\nFetchContent_GetProperties(xsmm)\nif(NOT xsmm_POPULATED)\n FetchContent_Populate(xsmm)\nendif()\n\nset(LIBXSMMROOT ${xsmm_SOURCE_DIR})\nfile(GLOB _GLOB_XSMM_SRCS LIST_DIRECTORIES false CONFIGURE_DEPENDS ${LIBXSMMROOT}/src/*.c)\nlist(REMOVE_ITEM _GLOB_XSMM_SRCS ${LIBXSMMROOT}/src/libxsmm_generator_gemm_driver.c)\nset(XSMM_INCLUDE_DIRS ${LIBXSMMROOT}/include)\n\nadd_library(xsmm STATIC ${_GLOB_XSMM_SRCS})\ntarget_include_directories(xsmm PUBLIC ${XSMM_INCLUDE_DIRS})\ntarget_compile_definitions(xsmm PUBLIC\n LIBXSMM_DEFAULT_CONFIG\n)\ntarget_compile_definitions(xsmm PRIVATE\n __BLAS=0\n)\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003einclude\u003c/span\u003e(FetchContent)\nFetchContent_Declare(\n xsmm\n URL https://github.com/chelini/libxsmm/archive/\u0026lt;your-preferred-revision\u0026gt;.tar.gz\n URL_HASH SHA256=\u0026lt;sha256sum-corresponding-to-above-revision\u0026gt;\n)\nFetchContent_GetProperties(xsmm)\n\u003cspan class=\"pl-k\"\u003eif\u003c/span\u003e(\u003cspan class=\"pl-k\"\u003eNOT\u003c/span\u003e xsmm_POPULATED)\n FetchContent_Populate(xsmm)\n\u003cspan class=\"pl-k\"\u003eendif\u003c/span\u003e()\n\n\u003cspan class=\"pl-k\"\u003eset\u003c/span\u003e(LIBXSMMROOT \u003cspan class=\"pl-k\"\u003e${xsmm_SOURCE_DIR}\u003c/span\u003e)\n\u003cspan class=\"pl-k\"\u003efile\u003c/span\u003e(GLOB _GLOB_XSMM_SRCS LIST_DIRECTORIES \u003cspan class=\"pl-k\"\u003efalse\u003c/span\u003e CONFIGURE_DEPENDS \u003cspan class=\"pl-k\"\u003e${LIBXSMMROOT}\u003c/span\u003e/src/*.c)\n\u003cspan class=\"pl-k\"\u003elist\u003c/span\u003e(REMOVE_ITEM _GLOB_XSMM_SRCS \u003cspan class=\"pl-k\"\u003e${LIBXSMMROOT}\u003c/span\u003e/src/libxsmm_generator_gemm_driver.c)\n\u003cspan class=\"pl-k\"\u003eset\u003c/span\u003e(XSMM_INCLUDE_DIRS \u003cspan class=\"pl-k\"\u003e${LIBXSMMROOT}\u003c/span\u003e/\u003cspan class=\"pl-e\"\u003einclude\u003c/span\u003e)\n\n\u003cspan class=\"pl-k\"\u003eadd_library\u003c/span\u003e(xsmm \u003cspan class=\"pl-e\"\u003eSTATIC\u003c/span\u003e \u003cspan class=\"pl-k\"\u003e${_GLOB_XSMM_SRCS}\u003c/span\u003e)\n\u003cspan class=\"pl-k\"\u003etarget_include_directories\u003c/span\u003e(xsmm \u003cspan class=\"pl-e\"\u003ePUBLIC\u003c/span\u003e \u003cspan class=\"pl-k\"\u003e${XSMM_INCLUDE_DIRS}\u003c/span\u003e)\n\u003cspan class=\"pl-k\"\u003etarget_compile_definitions\u003c/span\u003e(xsmm \u003cspan class=\"pl-e\"\u003ePUBLIC\u003c/span\u003e\n LIBXSMM_DEFAULT_CONFIG\n)\n\u003cspan class=\"pl-k\"\u003etarget_compile_definitions\u003c/span\u003e(xsmm \u003cspan class=\"pl-e\"\u003ePRIVATE\u003c/span\u003e\n __BLAS=0\n)\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eAbove, LIBXSMM_DEFAULT_CONFIG is propagated to dependent code (\u003ccode\u003ePUBLIC\u003c/code\u003e) and further, LIBXSMM is configured to not require a LAPACK/BLAS library/fallback (\u003ccode\u003e-D__BLAS=0\u003c/code\u003e).\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eLink Instructions\u003c/h2\u003e\u003ca id=\"user-content-link-instructions\" class=\"anchor\" aria-label=\"Permalink: Link Instructions\" href=\"#link-instructions\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eUsing the \u003ca href=\"#classic-library-abi\"\u003eclassic ABI\u003c/a\u003e (including \u003ca href=\"#fortran\"\u003eFortran\u003c/a\u003e code), requires linking LIBXSMM against the application. The library is agnostic with respect to the threading-runtime, and therefore an application is free to use any threading runtime (e.g., OpenMP). The library is also thread-safe, and multiple application threads can call LIBXSMM's routines concurrently. Enabling OpenMP for LIBXSMM's main library is supported as well (OMP=1), and mostly affects the synchronization primitives used inside of the library. All the \"omp\" functionality (function postfix) is served by the \u003ccode\u003elibxsmmext\u003c/code\u003e library, which is automatically built with OpenMP enabled. When using this \"omp\" functionality, \u003ccode\u003elibxsmmext\u003c/code\u003e needs to be present at the link line.\u003c/p\u003e\n\u003cmarkdown-accessiblity-table\u003e\u003ctable\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u003ca name=\"user-content-table-of-libraries\"\u003e\u003c/a\u003eLibrary\u003c/th\u003e\n\u003cth\u003ePurpose\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003elibxsmm\u003c/td\u003e\n\u003ctd\u003eThread-safe core functions (same routine can be called concurrently). Contains routines that can take a thread-ID and the number of library-external threads.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003elibxsmmf\u003c/td\u003e\n\u003ctd\u003eNecessary when using the Fortran MODule but not when including \u003ccode\u003elibxsmm.f\u003c/code\u003e or relying on implicit interfaces (\u003ca href=\"https://github.com/libxsmm/libxsmm/search?q=implementation+provided+for+Fortran+77+compatibility\"\u003eFortran 77\u003c/a\u003e).\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003elibxsmmext\u003c/td\u003e\n\u003ctd\u003eProvides library-internal OpenMP-threaded functions carrying the \u003ccode\u003eomp\u003c/code\u003e postfix when compared to function name names of the core library.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003elibxsmmnoblas\u003c/td\u003e\n\u003ctd\u003eSupplies faked symbols for \u003ccode\u003edgemm\u003c/code\u003e (and others) and thereby removes the need to link against a LAPACK/BLAS library.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\u003c/markdown-accessiblity-table\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-pkg-config\"\u003e\u003c/a\u003eTo ease linking with LIBXSMM, \u003ccode\u003epkg-config\u003c/code\u003e can be used. For example:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"export PKG_CONFIG_PATH=/path/to/libxsmm/lib\npkg-config libxsmm --libs\"\u003e\u003cpre\u003e\u003cspan class=\"pl-k\"\u003eexport\u003c/span\u003e PKG_CONFIG_PATH=/path/to/libxsmm/lib\npkg-config libxsmm --libs\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eSimilarly, an application is free to choose any BLAS or LAPACK library (if the link model available on the OS supports this), and therefore linking GEMM routines when linking LIBXSMM itself (by supplying BLAS=1|2) may prevent a user from making this decision at the time of linking the actual application. To use LIBXSMM without GEMM-related functionality, any BLAS-dependency can be removed in two ways: \u003cspan\u003e(1) building\u003c/span\u003e a special library with \u003ccode\u003emake BLAS=0\u003c/code\u003e, or \u003cspan\u003e(2) linking\u003c/span\u003e the application against the \u003ccode\u003elibxsmmnoblas\u003c/code\u003e library. If an application however uses BLAS already, the \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#call-wrapper\"\u003eCall Wrapper\u003c/a\u003e can be used to intercept existing BLAS calls (and to rely on LIBXSMM instead).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: LIBXSMM does not support to dynamically link \u003ccode\u003elibxsmm\u003c/code\u003e or \u003ccode\u003elibxsmmext\u003c/code\u003e (\"so\") when BLAS is linked statically (\"a\"). If BLAS is linked statically, the static version of LIBXSMM must be used!\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eInstallation\u003c/h3\u003e\u003ca id=\"user-content-installation\" class=\"anchor\" aria-label=\"Permalink: Installation\" href=\"#installation\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThere are two main mechanisms to install LIBXSMM (both mechanisms can be combined): \u003cspan\u003e(1) building\u003c/span\u003e the library in an \u003cspan\u003eout‑of‑tree\u003c/span\u003e fashion, and \u003cspan\u003e(2) installing\u003c/span\u003e into a certain location. \u003ca name=\"user-content-install-build\"\u003e\u003c/a\u003eBuilding in an \u003cspan\u003eout‑of‑tree\u003c/span\u003e fashion looks like:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"cd libxsmm-install\nmake -f /path/to/libxsmm/Makefile\"\u003e\u003cpre\u003e\u003cspan class=\"pl-c1\"\u003ecd\u003c/span\u003e libxsmm-install\nmake -f /path/to/libxsmm/Makefile\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-install-prefix\"\u003e\u003c/a\u003eInstallation into a specific location looks like (\u003ccode\u003ePREFIX\u003c/code\u003e or \u003ccode\u003eDESTDIR\u003c/code\u003e):\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make MNK=\u0026quot;1 2 3 4 5\u0026quot; PREFIX=/path/to/libxsmm-install install\"\u003e\u003cpre\u003emake MNK=\u003cspan class=\"pl-s\"\u003e\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e1 2 3 4 5\u003cspan class=\"pl-pds\"\u003e\"\u003c/span\u003e\u003c/span\u003e PREFIX=/path/to/libxsmm-install install\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-install-destdir\"\u003e\u003c/a\u003eBoth \u003ccode\u003ePREFIX\u003c/code\u003e and \u003ccode\u003eDESTDIR\u003c/code\u003e are equivalent and can be relative or absolute paths. An installation can be repeated for different locations without triggering a rebuild. The prefix directory \u003cem\u003einside\u003c/em\u003e of each of the \u003ca href=\"#pkg-config\"\u003epackage configuration files\u003c/a\u003e is set to where LIBXSMM is built (staging folder) unless \u003ccode\u003ePREFIX\u003c/code\u003e or \u003ccode\u003eDESTDIR\u003c/code\u003e is specified. The effect of \u003ccode\u003ePREFIX\u003c/code\u003e (or \u003ccode\u003eDESTDIR\u003c/code\u003e) with respect to the pkg-config files is independent of whether the install-target is invoked or not (make).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eFurther, performing \u003ccode\u003emake install-minimal\u003c/code\u003e omits the documentation (default: \u003ccode\u003ePREFIX/share/libxsmm\u003c/code\u003e). Moreover, PINCDIR, POUTDIR, PBINDIR, and PDOCDIR allow to customize the locations underneath of the PREFIX location. To build a general package for an unpredictable audience (Linux distribution, or similar), it is advised to not over-specify or customize the build step, i.e., JIT, SSE, AVX, OMP, BLAS, etc. should not be used. The following is building and installing a complete set of libraries where the generated interface matches both the static and the shared libraries:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make PREFIX=/path/to/libxsmm-install STATIC=0 install\nmake PREFIX=/path/to/libxsmm-install install\"\u003e\u003cpre\u003emake PREFIX=/path/to/libxsmm-install STATIC=0 install\nmake PREFIX=/path/to/libxsmm-install install\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eRuntime Control\u003ca name=\"user-content-running\"\u003e\u003c/a\u003e\u003c/h2\u003e\u003ca id=\"user-content-runtime-control\" class=\"anchor\" aria-label=\"Permalink: Runtime Control\" href=\"#runtime-control\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eHandling Errors\u003c/h3\u003e\u003ca id=\"user-content-handling-errors\" class=\"anchor\" aria-label=\"Permalink: Handling Errors\" href=\"#handling-errors\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe library handles errors with mechanisms available to the C programming language (no exceptions). The backend uses result codes passed by an argument rather than an actual return value. Such an argument is often a descriptor (struct) guiding and covering the state of the code generation. The frontend however may not hand-out any error state, which can be a big relief on the call-side. Instead, the frontend implements a \u003ca href=\"#verbose-mode\"\u003everbose mode\u003c/a\u003e to inform about unexpected input or an error captured from the backend. Guiding principles of LIBXSMM are muted operation by default (non-verbose) and no unexpected exit from execution.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eVerbose Mode\u003c/h3\u003e\u003ca id=\"user-content-verbose-mode\" class=\"anchor\" aria-label=\"Permalink: Verbose Mode\" href=\"#verbose-mode\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#getting-and-setting-the-verbosity\"\u003everbose mode\u003c/a\u003e (level of verbosity) allows for an insight into the code dispatch mechanism by receiving a small, tabulated statistic as soon as the library terminates. The design point for this functionality is to not impact the performance of any critical code path, i.e., verbose mode is always enabled and does not require symbols (SYM=1) or debug code (DBG=1). The statistics appears (\u003ccode\u003estderr\u003c/code\u003e) when the environment variable LIBXSMM_VERBOSE is set to a non-zero value. For example:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"LIBXSMM_VERBOSE=1 ./myapplication\n[... application output]\n\nHSW/SP TRY JIT STA COL\n 0..13 0 0 0 0\n 14..23 0 0 0 0\n 24..128 3 3 0 0\"\u003e\u003cpre\u003eLIBXSMM_VERBOSE=1 ./myapplication\n[... application output]\n\nHSW/SP TRY JIT STA COL\n 0..13 0 0 0 0\n 14..23 0 0 0 0\n 24..128 3 3 0 0\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThe tables are distinct between single-precision and double-precision, but either table is pruned if all counters are zero. If both tables are pruned, the library shows the code path which would have been used for JIT'ting the code: \u003ccode\u003eLIBXSMM_TARGET=hsw\u003c/code\u003e (otherwise the code path is shown in the table's header). The actual counters are collected for three buckets: small kernels (\u003cspan\u003eMNK\u003csup\u003e1/3\u003c/sup\u003e \u0026lt;= 13\u003c/span\u003e), medium-sized kernels (\u003cspan\u003e13 \u0026lt; MNK\u003csup\u003e1/3\u003c/sup\u003e \u0026lt;= 23\u003c/span\u003e), and larger kernels (\u003cspan\u003e23 \u0026lt; MNK\u003csup\u003e1/3\u003c/sup\u003e \u0026lt;= 64\u003c/span\u003e; the actual upper bound depends on LIBXSMM_MAX_MNK as selected at compile-time). Keep in mind, that \"larger\" is supposedly still small in terms of arithmetic intensity (which grows linearly with the kernel size). Unfortunately, the arithmetic intensity depends on the way a kernel is used (which operands are loaded/stored into main memory), and it is not performance-neutral to collect this information.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThe TRY counter represents all attempts to register statically generated kernels, and all attempts to dynamically generate and register kernels. The TRY counter includes rejected JIT requests due to unsupported GEMM arguments. The JIT and STA counters distinct the successful cases of the afore mentioned event (TRY) into dynamically (JIT) and statically (STA) generated code. In case the capacity (\u003cspan\u003eO(\u003cem\u003en\u003c/em\u003e) = 10\u003csup\u003e5\u003c/sup\u003e\u003c/span\u003e) of the code registry is exhausted, no more kernels can be registered although further attempts are not prevented. Registering many kernels (\u003cspan\u003eO(\u003cem\u003en\u003c/em\u003e) = 10\u003csup\u003e3\u003c/sup\u003e\u003c/span\u003e) may ramp the number of hash key collisions (COL), which can degrade performance. The latter is prevented if the small thread-local cache is utilized effectively.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eSince explicitly JIT-generated code (\u003ccode\u003elibxsmm_?mmdispatch\u003c/code\u003e) does not fall under the THRESHOLD criterion, the above table is extended by one line if large kernels have been requested. This indicates a missing threshold-criterion (customized dispatch) or asks for cache-blocking the matrix multiplication. Setting a verbosity level of at least two summarizes the number of registered JIT-generated kernels, which includes the total size and counters for GEMM, MCOPY (matrix copy), and TCOPY (matrix transpose) kernels.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"Registry: 20 MB (gemm=0 mcopy=14 tcopy=0)\"\u003e\u003cpre\u003eRegistry: 20 MB (gemm=0 mcopy=14 tcopy=0)\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eIf the call-wrapper is used, an additional runtime statistic becomes available (see \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#call-wrapper\"\u003eCall Wrapper\u003c/a\u003e).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-objdump\"\u003e\u003c/a\u003e\u003cstrong\u003eNote\u003c/strong\u003e: Setting LIBXSMM_VERBOSE to a negative value dumps each generated JIT kernel to a file (binary) with each file being named like the function name shown in \u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_prof.md#intelvtuneamplifier\"\u003eIntel VTune\u003c/a\u003e. Disassembly of the raw binary files can be accomplished by:\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"objdump -D -b binary -m i386 -M x86-64 [JIT-dump-file]\"\u003e\u003cpre\u003eobjdump -D -b binary -m i386 -M x86-64 [JIT-dump-file]\u003c/pre\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eCall Trace\u003c/h3\u003e\u003ca id=\"user-content-call-trace\" class=\"anchor\" aria-label=\"Permalink: Call Trace\" href=\"#call-trace\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eDuring the initial steps of employing the LIBXSMM API, one may rely on a debug version of the library (\u003ccode\u003emake DBG=1\u003c/code\u003e). The latter also implies console output (\u003ccode\u003estderr\u003c/code\u003e) in case of an error/warning condition inside of the library. It is also possible to print the execution flow (call trace) inside of LIBXSMM (can be combined with DBG=1 or OPT=0):\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"make TRACE=1\"\u003e\u003cpre\u003emake TRACE=1\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eBuilding an application which traces calls (inside of the library) requires the shared library of LIBXSMM, alternatively the application is required to link the static library of LIBXSMM in a dynamic fashion (GNU tool chain: \u003ccode\u003e-rdynamic\u003c/code\u003e). Tracing calls (without debugger) can be then accomplished by an environment variable called LIBXSMM_TRACE.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"LIBXSMM_TRACE=1 ./myapplication\"\u003e\u003cpre\u003eLIBXSMM_TRACE=1 ./myapplication\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eSyntactically up to three arguments separated by commas (which allows to omit arguments) are taken (\u003cem\u003etid\u003c/em\u003e,\u003cem\u003ei\u003c/em\u003e,\u003cem\u003en\u003c/em\u003e): \u003cem\u003etid\u003c/em\u003e signifies the ID of the thread to be traced with 1...NTHREADS being valid and where LIBXSMM_TRACE=1 is filtering for the \"main thread\" (in fact the first thread running into the trace facility); grabbing all threads (no filter) can be achieved by supplying a negative id (which is also the default when omitted). The second argument is pruning higher levels of the call-tree with \u003cem\u003ei=1\u003c/em\u003e being the default (level zero is the highest at the same level as the main function). The last argument is taking the number of inclusive call levels with \u003cem\u003en=-1\u003c/em\u003e being the default (signifying no filter).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eAlthough the \u003ccode\u003eltrace\u003c/code\u003e (Linux utility) provides similar insight, the trace facility might be useful due to the afore mentioned filtering expressions. Please note that the trace facility is severely impacting the performance (even with LIBXSMM_TRACE=0), and this is not just because of console output but rather since inlining (internal) functions might be prevented along with additional call overhead on each function entry and exit. Therefore, debug symbols can be also enabled separately (\u003ccode\u003emake SYM=1\u003c/code\u003e; implied by TRACE=1 or DBG=1) which might be useful when profiling an application.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eVerification\u003c/h3\u003e\u003ca id=\"user-content-verification\" class=\"anchor\" aria-label=\"Permalink: Verification\" href=\"#verification\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eThis section refers to testing correctness of an application using LIBXSMM utilities, i.e., using \u003ccode\u003elibxsmm_matdiff\u003c/code\u003e or \u003ccode\u003elibxsmm_matdiff_epsilon\u003c/code\u003e in particular. The former function (\u003ccode\u003elibxsmm_matdiff\u003c/code\u003e) compares two matrices (which can degenerate to vector shape), and yields a structure with information about the difference of both matrices (gold vs. test). The latter function (\u003ccode\u003elibxsmm_matdiff_epsilon\u003c/code\u003e) combines absolute and relative norms (given by afore mentioned structure) and calculates a scalar \"epsilon\" which can be used to check against a margin.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eUsing \u003ccode\u003elibxsmm_matdiff_epsilon\u003c/code\u003e in an application exposes an environment variable \u003ccode\u003eLIBXSMM_MATDIFF\u003c/code\u003e which can specify a file or directory path (\u003ccode\u003eLIBXSMM_MATDIFF=1\u003c/code\u003e simply uses some filename as default). In any case, the application appends one line to the respective file for each call of \u003ccode\u003elibxsmm_matdiff_epsilon\u003c/code\u003e. A data record consists of the epsilon and the command line used to launch the application. A generated file can be further evaluated, e.g., \u003ccode\u003esort -gk1 libxsmm_matdiff.log | tail -n 10\u003c/code\u003e which yields the largest ten epsilon values discovered along with the application's command line.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003eThe environment variable \u003ccode\u003eLIBXSMM_MATDIFF\u003c/code\u003e can carry optional space-separated arguments to amend each file entry like \u003ccode\u003eexport LIBXSMM_MATDIFF=\"libxsmm_matdiff.log hello world\"\u003c/code\u003e. In sophisticated cases this can be used to amend a value only known at runtime, e.g., the actual margin which is used to judge the epsilon (\u003ccode\u003eputenv\u003c/code\u003e).\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003ePerformance\u003c/h2\u003e\u003ca id=\"user-content-performance\" class=\"anchor\" aria-label=\"Permalink: Performance\" href=\"#performance\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-profiling\"\u003e\u003c/a\u003eProfiling an application, which uses LIBXSMM's JIT-code is well-supported. The library supports \u003cspan\u003eIntel VTune Amplifier\u003c/span\u003e and \u003cspan\u003eLinux perf\u003c/span\u003e. Details are given on how to include profiler support, and how to run the application.\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_prof.md#intelvtuneamplifier\"\u003eProfiling using Intel VTune Amplifier\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_prof.md#linuxperf\"\u003eProfiling using Linux perf\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-tuning\"\u003e\u003c/a\u003eAt build time, a variety of options exist to customize LIBXSMM. The library is setup for a broad range of use cases, which include sophisticated defaults for typical use.\u003c/p\u003e\n\u003cul dir=\"auto\"\u003e\n\u003cli\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_tune.md#tuning\"\u003eCustomizing performance\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca name=\"user-content-auto-dispatch\"\u003e\u003c/a\u003e\u003ca href=\"/libxsmm/libxsmm/blob/main/documentation/libxsmm_tune.md#auto-dispatch\"\u003eTuning auto-dispatch\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp dir=\"auto\"\u003e\u003ca name=\"user-content-results\"\u003e\u003c/a\u003eTo find performance results of applications or performance reproducers, the repository provides an orphaned branch called \"results\" which collects collateral material such as measured performance results along with explanatory figures. The results can be found at \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/results#libxsmm-results\"\u003ehttps://github.com/libxsmm/libxsmm/tree/results#libxsmm-results\u003c/a\u003e, or the results can be cloned as shown below.\u003c/p\u003e\n\u003cdiv class=\"highlight highlight-source-shell notranslate position-relative overflow-auto\" dir=\"auto\" data-snippet-clipboard-copy-content=\"git clone --branch results \\\n https://github.com/libxsmm/libxsmm.git \\\n libxsmm-results\"\u003e\u003cpre\u003egit clone --branch results \\\n https://github.com/libxsmm/libxsmm.git \\\n libxsmm-results\u003c/pre\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003ePlease note that comparing performance results depends on whether the operands of the matrix multiplication are streamed or not. For example, multiplying with all matrices covered by the L1 cache may have an emphasis towards an implementation which perhaps performs worse for the real workload (if this real workload needs to stream some or all matrices from the main memory). Most of the \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/samples\"\u003ecode samples\u003c/a\u003e are aimed to reproduce performance results, and it is encouraged to model the exact case or to look at real \u003ca href=\"#applications\"\u003eapplications\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eApplications\u003c/h2\u003e\u003ca id=\"user-content-applications\" class=\"anchor\" aria-label=\"Permalink: Applications\" href=\"#applications\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eHigh Performance Computing (HPC)\u003c/h3\u003e\u003ca id=\"user-content-high-performance-computing-hpc\" class=\"anchor\" aria-label=\"Permalink: High Performance Computing (HPC)\" href=\"#high-performance-computing-hpc\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[1] \u003c/b\u003e\u003ca href=\"https://cp2k.org/\" rel=\"nofollow\"\u003ehttps://cp2k.org/\u003c/a\u003e: Open Source Molecular Dynamics and the \u003ca href=\"https://github.com/cp2k/dbcsr\"\u003eDBCSR library\u003c/a\u003e, which processes batches of small matrix multiplications. The batches originate from a distributed block-sparse matrix with problem-specific small matrices. Starting with \u003ca href=\"https://www.cp2k.org/version_history\" rel=\"nofollow\"\u003eCP2K 3.0\u003c/a\u003e, LIBXSMM can substitute CP2K's \u003ccode\u003elibsmm\u003c/code\u003e library.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[2] \u003c/b\u003e\u003ca href=\"https://github.com/SeisSol/SeisSol/\"\u003ehttps://github.com/SeisSol/SeisSol/\u003c/a\u003e: SeisSol is one of the leading codes for earthquake scenarios, for simulating dynamic rupture processes. LIBXSMM provides highly optimized assembly kernels which form the computational back-bone of SeisSol (see \u003ca href=\"https://github.com/TUM-I5/seissol_kernels/\"\u003ehttps://github.com/TUM-I5/seissol_kernels/\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[3] \u003c/b\u003e\u003ca href=\"https://github.com/NekBox/NekBox\"\u003ehttps://github.com/NekBox/NekBox\u003c/a\u003e: NekBox is a highly scalable and portable spectral element code, which is inspired by the \u003ca href=\"https://nek5000.mcs.anl.gov/\" rel=\"nofollow\"\u003eNek5000\u003c/a\u003e code. NekBox is specialized for box geometries and intended to prototype new methods as well as to leverage FORTRAN beyond the FORTRAN 77 standard. LIBXSMM can be used to substitute the \u003ca href=\"https://github.com/Nek5000/NekBox/blob/box/mxm_std.F90\"\u003eMXM_STD\u003c/a\u003e code. Please also note LIBXSMM's \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/samples/nek#nek-sample-collection\"\u003eNekBox reproducer\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[4] \u003c/b\u003e\u003ca href=\"https://github.com/Nek5000/Nek5000\"\u003ehttps://github.com/Nek5000/Nek5000\u003c/a\u003e: Nek5000 is the open-source, highly-scalable, always-portable spectral element code from \u003ca href=\"https://nek5000.mcs.anl.gov/\" rel=\"nofollow\"\u003ehttps://nek5000.mcs.anl.gov/\u003c/a\u003e. The development branch of the Nek5000 code \u003ca href=\"https://github.com/Nek5000/Nek5000/blob/master/core/mxm_wrapper.f\"\u003eincorporates\u003c/a\u003e LIBXSMM.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[5] \u003c/b\u003e\u003ca href=\"http://pyfr.org/\" rel=\"nofollow\"\u003ehttp://pyfr.org/\u003c/a\u003e: PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures by using the flux reconstruction approach. PyFR 1.6.0 optionally \u003ca href=\"http://pyfr.org/user_guide.php\" rel=\"nofollow\"\u003eincorporates LIBXSMM\u003c/a\u003e as a matrix multiplication provider for the OpenMP backend. Please also note LIBXSMM's \u003ca href=\"https://github.com/libxsmm/libxsmm/tree/main/samples/pyfr\"\u003ePyFR-related code sample\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[6] \u003c/b\u003e\u003ca href=\"http://dial3343.org/about/\" rel=\"nofollow\"\u003ehttp://dial3343.org/about/\u003c/a\u003e: The Extreme-scale Discontinuous Galerkin Environment (EDGE) is a solver for hyperbolic partial differential equations with emphasis on seismic simulations. The EDGE \u003ca href=\"https://github.com/3343/edge\"\u003esource code\u003c/a\u003e optionally relies on LIBXSMM, but for high performance LIBXSMM's kernels are highly recommended.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[7] \u003c/b\u003e\u003ca href=\"https://sxs-collaboration.github.io/spectre/\" rel=\"nofollow\"\u003ehttps://sxs-collaboration.github.io/spectre/\u003c/a\u003e: SpECTRE is an open-source code for multi-scale, multi-physics problems in astrophysics and gravitational physics which runs at Petascale and is designed for Exascale computers. In the future, SpECTRE may be applied to problems across discipline boundaries in fluid dynamics, geoscience, plasma physics, nuclear physics, and engineering.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[8] \u003c/b\u003e\u003ca href=\"https://ceed.exascaleproject.org/ceed-code/\" rel=\"nofollow\"\u003ehttps://ceed.exascaleproject.org/ceed-code/\u003c/a\u003e: The Center for Efficient Exascale Discretizations (CEED) is building on the efforts of the Nek5000, MFEM, MAGMA, OCCA and PETSc projects to develop application program interfaces (APIs), both at high-level and at low-level to enable applications to take advantage of high-order methods. The CEED low-level API, \u003ca href=\"https://ceed.exascaleproject.org/libceed/\" rel=\"nofollow\"\u003elibCEED\u003c/a\u003e uses LIBXSMM as a \u003ca href=\"https://github.com/CEED/libCEED#backends\"\u003ebackend\u003c/a\u003e for high performance on CPUs.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[9] \u003c/b\u003e\u003ca href=\"https://github.com/romeric/Fastor\"\u003ehttps://github.com/romeric/Fastor\u003c/a\u003e: Fastor is a lightweight high performance tensor algebra framework for modern C++ and can optionally use LIBXSMM as \u003ca href=\"https://github.com/romeric/Fastor/wiki/9.-Using-the-LIBXSMM-MKL-JIT-backend\"\u003eJIT-backend\u003c/a\u003e.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eMachine Learning (ML)\u003c/h3\u003e\u003ca id=\"user-content-machine-learning-ml\" class=\"anchor\" aria-label=\"Permalink: Machine Learning (ML)\" href=\"#machine-learning-ml\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[10] \u003c/b\u003e\u003ca href=\"https://github.com/plaidml/plaidml\"\u003ehttps://github.com/plaidml/plaidml\u003c/a\u003e: PlaidML is an open source tensor compiler aiming for performance portability across a wide range of CPUs, GPUs and other accelerators. Combined with Intel’s nGraph compiler, PlaidML is targeting popular deep learning frameworks such as PyTorch, Keras (TensorFlow), and OpenVino. \u003ca href=\"https://github.com/plaidml/plaidml/tree/plaidml-v1\"\u003ePlaidML/v1\u003c/a\u003e (development branch) adopted \u003ca href=\"https://mlir.llvm.org/\" rel=\"nofollow\"\u003eMLIR\u003c/a\u003e, an extensible compiler infrastructure gaining industry-wide adoption. PlaidML/v1 started using LIBXSMM as backend for targeting CPUs.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[11] \u003c/b\u003e\u003ca href=\"https://github.com/intel/intel-extension-for-pytorch\"\u003ehttps://github.com/intel/intel-extension-for-pytorch\u003c/a\u003e: Intel Extension for PyTorch aims for a smooth user experience of PyTorch on CPUs by the means of good performance. The extension pack started to rely on \u003ca href=\"https://arxiv.org/abs/2005.04680\" rel=\"nofollow\"\u003eLIBXSMM for achieving high performance on CPUs\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[12] \u003c/b\u003e\u003ca href=\"https://github.com/libxsmm/tpp-pytorch-extension\"\u003ehttps://github.com/libxsmm/tpp-pytorch-extension\u003c/a\u003e: Intel(R) Tensor Processing Primitive Extension for pytorch is an open source software library the integrates Tensor Processing Primitives (\u003ca href=\"https://arxiv.org/abs/2104.05755\" rel=\"nofollow\"\u003eTPP\u003c/a\u003e) into pytorch. It is aiming for a smooth user experience of PyTorch on CPUs by the means of good performance. Intel's MLPerf Training submission codes leverage this \u003ca href=\"https://github.com/mlcommons/training_results.1/tree/main/Intel/benchmarks/bert/implementations/pytorch-cpu\"\u003eproject\u003c/a\u003e.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[13] \u003c/b\u003e\u003ca href=\"https://github.com/libxsmm/libxsmm-dnn\"\u003ehttps://github.com/libxsmm/libxsmm-dnn\u003c/a\u003e: LIBXSMM-DNN is an open source software library that demonstrates how Tensor Processing Primitives (\u003ca href=\"https://arxiv.org/abs/2104.05755\" rel=\"nofollow\"\u003eTPP\u003c/a\u003e) can be used to implement various deep learning primitives such as convolutions, linear layers or even pooling and norming. Due to the use of TPP not a single line of platform-specific code is needed.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch3 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eAutomated Driving (AD)\u003c/h3\u003e\u003ca id=\"user-content-automated-driving-ad\" class=\"anchor\" aria-label=\"Permalink: Automated Driving (AD)\" href=\"#automated-driving-ad\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[15] \u003c/b\u003e\u003ca href=\"https://software.seek.intel.com/accelerating-eigen-math-library\" rel=\"nofollow\"\u003ehttps://software.seek.intel.com/accelerating-eigen-math-library\u003c/a\u003e: Accelerating The Eigen Math Library for Automated Driving Workloads: The Need for Speed in Kalman Filtering. An article in \u003ca href=\"https://software.intel.com/content/www/us/en/develop/download/parallel-universe-magazine-issue-31-january-2018.html\" rel=\"nofollow\"\u003eIssue 31\u003c/a\u003e of The Parallel Universe magazine (\u003ca href=\"https://software.intel.com/content/dam/develop/public/us/en/documents/parallel-universe-issue-31.pdf\" rel=\"nofollow\"\u003epdf\u003c/a\u003e).\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eReferences\u003c/h2\u003e\u003ca id=\"user-content-references\" class=\"anchor\" aria-label=\"Permalink: References\" href=\"#references\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[1] \u003c/b\u003e\u003ca href=\"https://sc19.supercomputing.org/proceedings/tech_poster/tech_poster_pages/rpost244.html\" rel=\"nofollow\"\u003ehttps://sc19.supercomputing.org/proceedings/tech_poster/tech_poster_pages/rpost244.html\u003c/a\u003e: High-Performance Deep Learning via a Single Building Block (\u003ca href=\"https://sc19.supercomputing.org/proceedings/tech_poster/poster_files/rpost244s2-file2.pdf\" rel=\"nofollow\"\u003eposter\u003c/a\u003e and \u003ca href=\"https://sc19.supercomputing.org/proceedings/tech_poster/poster_files/rpost244s2-file3.pdf\" rel=\"nofollow\"\u003eabstract\u003c/a\u003e), SC’19: The International Conference for High Performance Computing, Networking, Storage, and Analysis, Denver (Colorado).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[2] \u003c/b\u003e\u003ca href=\"https://dl.acm.org/doi/10.1109/SC.2018.00069\" rel=\"nofollow\"\u003ehttps://dl.acm.org/doi/10.1109/SC.2018.00069\u003c/a\u003e: Anatomy of High-Performance Deep Learning Convolutions on SIMD Architectures (\u003ca href=\"https://arxiv.org/pdf/1808.05567.pdf\" rel=\"nofollow\"\u003epaper\u003c/a\u003e). SC'18: The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas (Texas).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[3] \u003c/b\u003e\u003ca href=\"https://pasc17.pasc-conference.org/fileadmin/user_upload/pasc17/program/post116s2.pdf\" rel=\"nofollow\"\u003ehttps://pasc17.pasc-conference.org/fileadmin/user_upload/pasc17/program/post116s2.pdf\u003c/a\u003e: DBCSR: A Sparse Matrix Multiplication Library for Electronic Structure Codes (poster), PASC’17: The PASC17 Conference, Lugano (Switzerland).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[4] \u003c/b\u003e\u003ca href=\"https://sc17.supercomputing.org/SC17%20Archive/tech_poster/tech_poster_pages/post190.html\" rel=\"nofollow\"\u003ehttps://sc17.supercomputing.org/SC17%20Archive/tech_poster/tech_poster_pages/post190.html\u003c/a\u003e: Understanding the Performance of Small Convolution Operations for CNN on Intel Architecture (\u003ca href=\"https://sc17.supercomputing.org/SC17%20Archive/tech_poster/poster_files/post190s2-file2.pdf\" rel=\"nofollow\"\u003eposter\u003c/a\u003e and \u003ca href=\"https://sc17.supercomputing.org/SC17%20Archive/tech_poster/poster_files/post190s2-file3.pdf\" rel=\"nofollow\"\u003eabstract\u003c/a\u003e), SC’17: The International Conference for High Performance Computing, Networking, Storage, and Analysis, Denver (Colorado).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[5] \u003c/b\u003e\u003ca href=\"https://www.computer.org/csdl/proceedings-article/sc/2016/8815a981/12OmNCeaQ1D\" rel=\"nofollow\"\u003ehttps://www.computer.org/csdl/proceedings-article/sc/2016/8815a981/12OmNCeaQ1D\u003c/a\u003e: LIBXSMM: Accelerating Small Matrix Multiplications by Runtime Code Generation. SC'16: The International Conference for High Performance Computing, Networking, Storage and Analysis, Salt Lake City (Utah).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[6] \u003c/b\u003e\u003ca href=\"http://sc15.supercomputing.org/sites/all/themes/SC15images/tech_poster/tech_poster_pages/post137.html\" rel=\"nofollow\"\u003ehttp://sc15.supercomputing.org/sites/all/themes/SC15images/tech_poster/tech_poster_pages/post137.html\u003c/a\u003e: LIBXSMM: A High Performance Library for Small Matrix Multiplications (\u003ca href=\"http://sc15.supercomputing.org/sites/all/themes/SC15images/tech_poster/poster_files/post137s2-file2.pdf\" rel=\"nofollow\"\u003eposter\u003c/a\u003e and \u003ca href=\"http://sc15.supercomputing.org/sites/all/themes/SC15images/tech_poster/poster_files/post137s2-file3.pdf\" rel=\"nofollow\"\u003eabstract\u003c/a\u003e). SC'15: The International Conference for High Performance Computing, Networking, Storage and Analysis, Austin (Texas).\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[7] \u003c/b\u003e\u003ca href=\"https://arxiv.org/abs/2104.05755\" rel=\"nofollow\"\u003eTensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning \u0026amp; HPC Workloads\u003c/a\u003e SC'21: The International Conference for High Performance Computing, Networking, Storage and Analysis, St Louis.\u003c/p\u003e\n\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch2 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eArticles\u003c/h2\u003e\u003ca id=\"user-content-articles\" class=\"anchor\" aria-label=\"Permalink: Articles\" href=\"#articles\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[1] \u003c/b\u003e\u003ca href=\"https://www.nextplatform.com/2019/10/09/cloudy-supercomputers-join-the-hpc-petascale-club/\" rel=\"nofollow\"\u003ehttps://www.nextplatform.com/2019/10/09/cloudy-supercomputers-join-the-hpc-petascale-club/\u003c/a\u003e: Cloudy Supercomputers Join the HPC Petascale Club. An article written by Rob Farber, 2019. The article covers LIBXSMM in a separate section.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[2] \u003c/b\u003e\u003ca href=\"https://www.nextplatform.com/2019/06/26/counting-the-cost-of-scaling-hpc-applications/\" rel=\"nofollow\"\u003ehttps://www.nextplatform.com/2019/06/26/counting-the-cost-of-scaling-hpc-applications/\u003c/a\u003e: Counting The Cost Of Scaling HPC Applications. An article written by Timothy Prickett Morgan, 2019. This article is about CP2K Open Source Molecular Dynamics and not about LIBXSMM. However, LIBXSMM was key for application performance.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[3] \u003c/b\u003e\u003ca href=\"https://www.nextplatform.com/2019/06/26/counting-the-cost-of-scaling-hpc-applications/\" rel=\"nofollow\"\u003ehttps://www.nextplatform.com/2019/06/26/counting-the-cost-of-scaling-hpc-applications/\u003c/a\u003e: Azure Benchmarks HC-series Across Twenty-thousand Cores for HPC. An article written by John Russell, 2019. This article is about CP2K Open Source Molecular Dynamics and not about LIBXSMM. However, LIBXSMM was key for application performance.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[4] \u003c/b\u003e\u003ca href=\"https://software.intel.com/content/www/us/en/develop/download/parallel-universe-magazine-issue-34-october-2018.html\" rel=\"nofollow\"\u003ehttps://software.intel.com/sites/default/files/parallel-universe-issue-34.pdf\u003c/a\u003e: LIBXSMM: An Open Source-Based Inspiration for Hardware and Software Development at Intel (\u003ca href=\"https://software.intel.com/content/dam/develop/public/us/en/documents/parallel-universe-issue-34.pdf\" rel=\"nofollow\"\u003epdf\u003c/a\u003e). An article written by Hans Pabst, Greg Henry, and Alexander Heinecke, 2018.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[5] \u003c/b\u003e\u003ca href=\"https://medium.com/@rmfarber/libxsmm-brings-deep-learning-lessons-learned-to-many-hpc-applications-9143c6c93125\" rel=\"nofollow\"\u003ehttps://medium.com/@rmfarber/libxsmm-brings-deep-learning-lessons-learned-to-many-hpc-applications-9143c6c93125\u003c/a\u003e: LIBXSMM Brings Deep-learning \"Lessons Learned\" to Many HPC Applications. An article written by Rob Farber, 2018.\u003c/p\u003e\n\u003cp dir=\"auto\"\u003e\u003cb\u003e[6] \u003c/b\u003e\u003ca href=\"https://www.rdworldonline.com/largest-supercomputer-simulation-of-sumatra-andaman-earthquake/\" rel=\"nofollow\"\u003ehttps://www.rdworldonline.com/largest-supercomputer-simulation-of-sumatra-andaman-earthquake/\u003c/a\u003e: Largest Supercomputer Simulation of Sumatra-Andaman Earthquake. An article written by Linda Barney, 2018.\u003c/p\u003e\n\u003c/article\u003e","loaded":true,"timedOut":false,"errorMessage":null,"headerInfo":{"toc":[{"level":1,"text":"LIBXSMM","anchor":"libxsmm","htmlText":"LIBXSMM"},{"level":2,"text":"Interfaces and Domains","anchor":"interfaces-and-domains","htmlText":"Interfaces and Domains"},{"level":3,"text":"Overview","anchor":"overview","htmlText":"Overview"},{"level":3,"text":"Matrix Multiplication","anchor":"matrix-multiplication","htmlText":"Matrix Multiplication"},{"level":3,"text":"Deep Learning","anchor":"deep-learning","htmlText":"Deep Learning"},{"level":3,"text":"Service Functions","anchor":"service-functions","htmlText":"Service Functions"},{"level":3,"text":"Backend","anchor":"backend","htmlText":"Backend"},{"level":2,"text":"Build Instructions","anchor":"build-instructions","htmlText":"Build Instructions"},{"level":3,"text":"Overview","anchor":"overview-1","htmlText":"Overview"},{"level":3,"text":"Classic Library (ABI)","anchor":"classic-library-abi","htmlText":"Classic Library (ABI)"},{"level":3,"text":"Header-Only","anchor":"header-only","htmlText":"Header-Only"},{"level":2,"text":"Rules for building LIBXSMM","anchor":"rules-for-building-libxsmm","htmlText":"Rules for building LIBXSMM"},{"level":2,"text":"Link Instructions","anchor":"link-instructions","htmlText":"Link Instructions"},{"level":3,"text":"Installation","anchor":"installation","htmlText":"Installation"},{"level":2,"text":"Runtime Control","anchor":"runtime-control","htmlText":"Runtime Control"},{"level":3,"text":"Handling Errors","anchor":"handling-errors","htmlText":"Handling Errors"},{"level":3,"text":"Verbose Mode","anchor":"verbose-mode","htmlText":"Verbose Mode"},{"level":3,"text":"Call Trace","anchor":"call-trace","htmlText":"Call Trace"},{"level":3,"text":"Verification","anchor":"verification","htmlText":"Verification"},{"level":2,"text":"Performance","anchor":"performance","htmlText":"Performance"},{"level":2,"text":"Applications","anchor":"applications","htmlText":"Applications"},{"level":3,"text":"High Performance Computing (HPC)","anchor":"high-performance-computing-hpc","htmlText":"High Performance Computing (HPC)"},{"level":3,"text":"Machine Learning (ML)","anchor":"machine-learning-ml","htmlText":"Machine Learning (ML)"},{"level":3,"text":"Automated Driving (AD)","anchor":"automated-driving-ad","htmlText":"Automated Driving (AD)"},{"level":2,"text":"References","anchor":"references","htmlText":"References"},{"level":2,"text":"Articles","anchor":"articles","htmlText":"Articles"}],"siteNavLoginPath":"/login?return_to=https%3A%2F%2Fgithub.com%2Flibxsmm%2Flibxsmm"}},{"displayName":"CODE_OF_CONDUCT.md","repoName":"libxsmm","refName":"main","path":"CODE_OF_CONDUCT.md","preferredFileType":"code_of_conduct","tabName":"Code of 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src="https://camo.githubusercontent.com/2bb59a49fb2b2cf62074495331376db0469d09c5b3c1c9d66ec527cf12ae2e2f/68747470733a2f2f72656164746865646f63732e6f72672f70726f6a656374732f6c696278736d6d2f62616467652f3f76657273696f6e3d6c6174657374" alt="Read the Docs" title="Read the Docs" data-canonical-src="https://readthedocs.org/projects/libxsmm/badge/?version=latest" style="max-width: 100%;"></a></p> <p dir="auto">LIBXSMM is a library for specialized dense and sparse matrix operations as well as for deep learning primitives such as small convolutions. The library is targeting Intel Architecture with <span>Intel SSE</span>, <span>Intel AVX</span>, <span>Intel AVX2</span>, <span>Intel AVX‑512</span> (with VNNI and Bfloat16), and <span>Intel AMX</span> (Advanced Matrix Extensions) supported by future Intel processor code-named Sapphire Rapids. Code generation is mainly based on <span>Just‑In‑Time (JIT)</span> code specialization for compiler-independent performance (matrix multiplications, matrix transpose/copy, sparse functionality, and deep learning). LIBXSMM is suitable for "build once and deploy everywhere", i.e., no special target flags are needed to exploit the available performance. Supported GEMM datatypes are: <code>FP64</code>, <code>FP32</code>, <code>bfloat16</code>, <code>int16</code>, and <code>int8</code>.</p> <p dir="auto">For a list questions and answers, please also have a look at <a href="https://github.com/libxsmm/libxsmm/wiki/Q&A">https://github.com/libxsmm/libxsmm/wiki/Q&A</a>.</p> <p dir="auto"><strong>Where to go for documentation?</strong></p> <ul dir="auto"> <li><strong>ReadtheDocs</strong>: <a href="https://libxsmm.readthedocs.io/" rel="nofollow">main</a> and <a href="https://libxsmm.readthedocs.io/libxsmm_samples/" rel="nofollow">sample</a> documentation with full text search.</li> <li><strong>PDF</strong>: <a href="https://github.com/libxsmm/libxsmm/raw/main/documentation/libxsmm.pdf">main</a> documentation file, and separate <a href="https://github.com/libxsmm/libxsmm/raw/main/documentation/libxsmm_samples.pdf">sample</a> documentation.</li> <li><strong>Articles</strong>: <a href="https://software.intel.com/sites/default/files/parallel-universe-issue-34.pdf" rel="nofollow">magazine article</a> incl. <a href="https://github.com/libxsmm/libxsmm/tree/main/samples/magazine">sample code</a> (full list of <a href="#articles">Articles</a>).</li> </ul> <p dir="auto"><a name="user-content-getting-started"></a><a name="user-content-hello-libxsmm"></a><strong>Getting Started</strong>: The following C++ code is focused on a specific functionality but may be considered as <a href="https://github.com/libxsmm/libxsmm/tree/main/samples/hello">Hello LIBXSMM</a>. Build the example with <code>cd /path/to/libxsmm; make STATIC=0</code> (shared library), save the code under <code>hello.cpp</code> (below) and compile with <code>g++ -I/path/to/libxsmm/include hello.cpp -L/path/to/libxsmm/lib -lxsmm -lblas -o hello</code> (GNU CCC), and finally execute with <code>LD_LIBRARY_PATH=/path/to/libxsmm/lib LIBXSMM_VERBOSE=2 ./hello</code>.</p> <div class="highlight highlight-source-c++ notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="#include <libxsmm.h> #include <vector> int main(int argc, char* argv[]) { typedef double T; int batchsize = 1000, m = 13, n = 5, k = 7; std::vector<T> a(batchsize * m * k), b(batchsize * k * n), c(m * n, 0); /* C/C++ and Fortran interfaces are available */ typedef libxsmm_mmfunction<T> kernel_type; /* generates and dispatches a matrix multiplication kernel (C++ functor) */ kernel_type kernel(LIBXSMM_GEMM_FLAG_NONE, m, n, k, 1.0 /*alpha*/, 1.0 /*beta*/); assert(kernel); for (int i = 0; i < batchsize; ++i) { /* initialize input */ for (int ki = 0; ki < k; ++ki) { for (int j = 0; j < m; ++j) a[i * j * ki] = static_cast<T>(1) / ((i + j + ki) % 25); for (int j = 0; j < n; ++j) b[i * j * ki] = static_cast<T>(7) / ((i + j + ki) % 75); } } /* kernel multiplies and accumulates matrices: C += Ai * Bi */ for (int i = 0; i < batchsize; ++i) kernel(&a[i * m * k], &b[i * k * n], &c[0]); }"><pre>#<span class="pl-k">include</span> <span class="pl-s"><span class="pl-pds"><</span>libxsmm.h<span class="pl-pds">></span></span> #<span class="pl-k">include</span> <span class="pl-s"><span class="pl-pds"><</span>vector<span class="pl-pds">></span></span> <span class="pl-k">int</span> <span class="pl-en">main</span>(<span class="pl-k">int</span> argc, <span class="pl-k">char</span>* argv[]) { <span class="pl-k">typedef</span> <span class="pl-k">double</span> T; <span class="pl-k">int</span> batchsize = <span class="pl-c1">1000</span>, m = <span class="pl-c1">13</span>, n = <span class="pl-c1">5</span>, k = <span class="pl-c1">7</span>; std::vector<T> <span class="pl-c1">a</span>(batchsize * m * k), <span class="pl-c1">b</span>(batchsize * k * n), <span class="pl-c1">c</span>(m * n, <span class="pl-c1">0</span>); <span class="pl-c"><span class="pl-c">/*</span> C/C++ and Fortran interfaces are available <span class="pl-c">*/</span></span> <span class="pl-k">typedef</span> libxsmm_mmfunction<T> kernel_type; <span class="pl-c"><span class="pl-c">/*</span> generates and dispatches a matrix multiplication kernel (C++ functor) <span class="pl-c">*/</span></span> kernel_type <span class="pl-smi">kernel</span>(LIBXSMM_GEMM_FLAG_NONE, m, n, k, <span class="pl-c1">1.0</span> <span class="pl-c"><span class="pl-c">/*</span>alpha<span class="pl-c">*/</span></span>, <span class="pl-c1">1.0</span> <span class="pl-c"><span class="pl-c">/*</span>beta<span class="pl-c">*/</span></span>); <span class="pl-c1">assert</span>(kernel); <span class="pl-k">for</span> (<span class="pl-k">int</span> i = <span class="pl-c1">0</span>; i < batchsize; ++i) { <span class="pl-c"><span class="pl-c">/*</span> initialize input <span class="pl-c">*/</span></span> <span class="pl-k">for</span> (<span class="pl-k">int</span> ki = <span class="pl-c1">0</span>; ki < k; ++ki) { <span class="pl-k">for</span> (<span class="pl-k">int</span> j = <span class="pl-c1">0</span>; j < m; ++j) a[i * j * ki] = <span class="pl-k">static_cast</span><T>(<span class="pl-c1">1</span>) / ((i + j + ki) % <span class="pl-c1">25</span>); <span class="pl-k">for</span> (<span class="pl-k">int</span> j = <span class="pl-c1">0</span>; j < n; ++j) b[i * j * ki] = <span class="pl-k">static_cast</span><T>(<span class="pl-c1">7</span>) / ((i + j + ki) % <span class="pl-c1">75</span>); } } <span class="pl-c"><span class="pl-c">/*</span> kernel multiplies and accumulates matrices: C += Ai * Bi <span class="pl-c">*/</span></span> <span class="pl-k">for</span> (<span class="pl-k">int</span> i = <span class="pl-c1">0</span>; i < batchsize; ++i) <span class="pl-c1">kernel</span>(&a[i * m * k], &b[i * k * n], &c[<span class="pl-c1">0</span>]); }</pre></div> <p dir="auto">Plain <a href="https://github.com/libxsmm/libxsmm/blob/main/samples/hello/hello.c">C code</a> as well as <a href="https://github.com/libxsmm/libxsmm/blob/main/samples/hello/hello.f">Fortran code</a> resemble the same <a href="https://github.com/libxsmm/libxsmm/tree/main/samples/hello">example</a>.</p> <p dir="auto"><a name="user-content-what-is-a-small-matrix-multiplication"></a><strong>What is a small matrix multiplication?</strong> When characterizing the problem-size by using the M, N, and K parameters, a problem-size suitable for LIBXSMM falls approximately within <i>(M N K)<sup>1/3</sup> <= 64</i> (which illustrates that non-square matrices or even "tall and skinny" shapes are covered as well). The library is typically used to generate code up to the specified <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_tune.md#auto-dispatch">threshold</a>. Raising the threshold may not only generate excessive amounts of code (due to unrolling in M or K dimension), but also miss to implement a tiling scheme to effectively utilize the cache hierarchy. For auto-dispatched problem-sizes above the configurable threshold (explicitly JIT'ted code is <strong>not</strong> subject to the threshold), LIBXSMM is falling back to BLAS. In terms of GEMM, the supported kernels are limited to <em>Alpha := 1</em>, <em>Beta := { 1, 0 }</em>, and <em>TransA := 'N'</em>.</p> <p dir="auto"><a name="user-content-what-is-a-small-convolution"></a><strong>What is a small convolution?</strong> In the last years, new workloads such as deep learning and more specifically convolutional neural networks (CNN) emerged and are pushing the limits of today's hardware. One of the expensive kernels is a small convolution with certain kernel sizes such that calculations in the frequency space is not the most efficient method when compared with direct convolutions. LIBXSMM's current support for convolutions aims for an easy-to-use invocation of small (direct) convolutions, which are intended for CNN training and classification.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Interfaces and Domains<a name="user-content-interfaces"></a></h2><a id="user-content-interfaces-and-domains" class="anchor" aria-label="Permalink: Interfaces and Domains" href="#interfaces-and-domains"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Overview<a name="user-content-general-interface"></a></h3><a id="user-content-overview" class="anchor" aria-label="Permalink: Overview" href="#overview"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Please have a look at <a href="https://github.com/libxsmm/libxsmm/tree/main/include">https://github.com/libxsmm/libxsmm/tree/main/include</a> for all published functions. Get started with the following list of available domains and documented functionality:</p> <ul dir="auto"> <li>MM: <a href="#matrix-multiplication">Matrix Multiplication</a></li> <li>TPP: <a href="/libxsmm/libxsmm/blob/main/libxsmm_tpp.md">Tensor Processing Primitives</a></li> <li>DNN: <a href="#deep-neural-networks">Deep Neural Networks</a></li> <li>AUX: <a href="#service-functions">Service Functions</a></li> <li>PERF: <a href="#performance">Performance</a></li> <li>BE: <a href="#jit-backend">Backend</a></li> </ul> <p dir="auto">To initialize library internal resources, an explicit initialization routine helps to avoid lazy initialization overhead when calling LIBXSMM for the first time. The library deallocates internal resources at program exit, but also provides a companion of the afore mentioned initialization (finalize).</p> <div class="highlight highlight-source-c notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="/** Initialize the library; pay for setup cost at a specific point. */ void libxsmm_init(void); /** De-initialize the library and free internal memory (optional). */ void libxsmm_finalize(void);"><pre><span class="pl-c">/** Initialize the library; pay for setup cost at a specific point. */</span> <span class="pl-smi">void</span> <span class="pl-en">libxsmm_init</span>(<span class="pl-smi">void</span>); <span class="pl-c">/** De-initialize the library and free internal memory (optional). */</span> <span class="pl-smi">void</span> <span class="pl-en">libxsmm_finalize</span>(<span class="pl-smi">void</span>);</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Matrix Multiplication<a name="user-content-interface-for-matrix-multiplication"></a></h3><a id="user-content-matrix-multiplication" class="anchor" aria-label="Permalink: Matrix Multiplication" href="#matrix-multiplication"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">This domain (MM) supports Small Matrix Multiplications (SMM), batches of multiple multiplications as well as the industry-standard interface for GEneral Matrix Matrix multiplication (GEMM).</p> <p dir="auto">The <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md">Matrix Multiplication domain (MM)</a> contains routines for:</p> <ul dir="auto"> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#overview">Small, tiled, and parallelized matrix multiplications</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#manual-code-dispatch">Manual code dispatch (customized matrix batches)</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#batched-multiplication">Batched multiplication (explicit interface)</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#call-wrapper">Call wrapper (static and dynamic linkage)</a></li> </ul> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Deep Learning<a name="user-content-interface-for-dl"></a></h3><a id="user-content-deep-learning" class="anchor" aria-label="Permalink: Deep Learning" href="#deep-learning"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">The Deep Learning domain is detailed by the following <a href="https://github.com/libxsmm/libxsmm/tree/main/samples/deeplearning">sample codes</a>. Here we demonstrate how common operators in deep learning applications (GEMM with activation function fusion, Convolutions with activation function fusion, various norming operators, and pooling operators, etc.) can be implemented using the Tensor Processing Primitive provided by LIBXSMM. Example drivers for performance evaluation are provided as part of <a href="https://github.com/libxsmm/libxsmm-dnn/tree/main/tests">LIBXSMM_DNN</a>.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Service Functions</h3><a id="user-content-service-functions" class="anchor" aria-label="Permalink: Service Functions" href="#service-functions"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">For convenient operation of the library and to ease integration, some service routines are available. These routines may not belong to the core functionality of LIBXSMM (SMM or DNN domain), but users are encouraged to use this domain (AUX). There are two categories: <span>(1) routines</span> which are available for C and FORTRAN, and <span>(2) routines</span> that are only available per C interface.</p> <p dir="auto">The <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md">service function domain (AUX)</a> contains routines for:</p> <ul dir="auto"> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#getting-and-setting-the-target-architecture">Getting and setting the target architecture</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#getting-and-setting-the-verbosity">Getting and setting the verbosity</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#timer-facility">Measuring time durations (timer)</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#user-data-dispatch">Dispatching user-data and multiple kernels</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#meta-image-file-io">Loading and storing data (I/O)</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#memory-allocation">Allocating memory</a></li> </ul> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Backend<a name="user-content-jit-backend"></a></h3><a id="user-content-backend" class="anchor" aria-label="Permalink: Backend" href="#backend"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">More information about the JIT-backend and the code generator can be found in a separate <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_be.md">document</a>. The <a href="https://github.com/libxsmm/libxsmm/tree/main/samples/encoder">encoder sample collection</a> can help to get started writing a kernel using LIBXSMM. Please note, LIBXSMM's stand-alone <a name="user-content-generator-driver"></a><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_be.md#generator-driver">generator-driver</a> is considered legacy (deprecated).</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Build Instructions</h2><a id="user-content-build-instructions" class="anchor" aria-label="Permalink: Build Instructions" href="#build-instructions"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Overview</h3><a id="user-content-overview-1" class="anchor" aria-label="Permalink: Overview" href="#overview-1"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">The main interface file is <em>generated</em>, and it is therefore <strong>not</strong> stored in the code repository. To inspect the interface for <a href="https://github.com/libxsmm/libxsmm/blob/main/src/template/libxsmm.h">C/C++</a> and <a href="https://github.com/libxsmm/libxsmm/blob/main/src/template/libxsmm.f">FORTRAN</a>, one can take a look at the template files used to generate the actual interface. There are two general ways to build and use LIBXSMM:</p> <ul dir="auto"> <li><a href="#classic-library-abi">Classic Library (ABI)</a> and <a href="#link-instructions">Link Instructions</a> (C/C++ and FORTRAN)</li> <li><a href="#header-only">Header-Only</a> (C and C++)</li> </ul> <p dir="auto"><strong>Note</strong>: LIBXSMM is available as prebuilt package for Fedora/RedHat/CentOS, Debian/Ubuntu, FreeBSD, and others. Further, LIBXSMM can be installed with the <a href="https://computing.llnl.gov/projects/spack-hpc-package-manager" rel="nofollow">Spack Package Manager</a> or per <a href="https://github.com/easybuilders">EasyBuild+EasyConfig</a>.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Classic Library (ABI)</h3><a id="user-content-classic-library-abi" class="anchor" aria-label="Permalink: Classic Library (ABI)" href="#classic-library-abi"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">There are two ways to rely on prebuilt code for a given project: <span>(1) using</span> LIBXSMM's Makefile based build system, <span>(2) or</span> using another build system and writing own <a href="#rules-for-building-libxsmm">rules for building LIBXSMM</a>. The Makefile based build system relies on <span>GNU Make</span> (typically associated with the <code>make</code> command, but e.g. FreeBSD is calling it <code>gmake</code>). The build can be customized by using <span>key‑value</span> pairs. <span>Key‑value</span> pairs can be supplied in two ways: <span>(1) after</span> the "make" command, or <span>(2) prior</span> to the "make" command (<code>env</code>) which is effectively the same as exporting the <span>key‑value</span> pair as an environment variable (<code>export</code>, or <code>setenv</code>). Both methods can be mixed (the second method may require make's <code>-e</code> flag).</p> <p dir="auto"><a name="user-content-zero-config-abi"></a>In contrast to <a href="#zero-config">header-only</a> which does not require configuration by default, 3rd-party build systems can compile and link LIBXSMM's sources but still avoid configuring the library (per <code>libxsmm_config.py</code>). The prerequisite to omit configuration is to opt-in by defining LIBXSMM_DEFAULT_CONFIG (<code>-D</code>). The zero-config feature is not available for LIBXSMM's Fortran interface.</p> <p dir="auto"><strong>Note</strong>: By default, C/C++ and FORTRAN compilers are needed (some sample code is written in C++). Beside of specifying the compilers (<code>make CXX=g++ CC=gcc FC=gfortran</code> and maybe <code>AR=ar</code>), the need for a FORTRAN compiler can be relaxed (<code>make FC=</code> or <code>make FORTRAN=0</code>). The latter affects the availability of the MODule file and the corresponding <code>libxsmm.f</code> library (the interface <code>libxsmm.f</code> is still generated).</p> <p dir="auto">The build system considers a set of given key-value pairs as a single unique build and triggers a rebuild for a distinct set of flags. For more advanced builds or additional background, please consult the section about <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_tune.md">Customization</a>. To generate the interface of the library inside of the <code>include</code> directory and to build the static library (by default, STATIC=1 is activated). Run any (or both) of the following command(s):</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make STATIC=0 make"><pre>make STATIC=0 make</pre></div> <p dir="auto">On CRAY systems, the CRAY Compiling Environment (CCE) should be used regardless of utilizing the CRAY compiler, the Intel Compiler, or the <span>GNU Compiler Collection (GCC)</span>. The CCE is eventually suppressing to build shared libraries (STATIC=0). In any case, <span>(1) switch</span> to the desired compiler (module load/switch), and <span>(2) rely</span> on:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make CXX=CC CC=cc FC=ftn"><pre>make CXX=CC CC=cc FC=ftn</pre></div> <p dir="auto">A variety of build environments is out-of-the-box compatible, see <a href="https://github.com/libxsmm/libxsmm/wiki/Compatibility">https://github.com/libxsmm/libxsmm/wiki/Compatibility</a>. If the build process is not successful, it may help to avoid advanced GCC flags. This is useful with a tool chain, which pretends to be GCC-compatible (and is treated as such) but fails to consume the afore mentioned flags:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make COMPATIBLE=1"><pre>make COMPATIBLE=1</pre></div> <p dir="auto"><a name="user-content-outdated-binutils"></a>In case of outdated Binutils, compilation can fail to assemble code when building the library (this has nothing to do with JIT-generated code and it does not affect how JIT-code is targeting the system). LIBXSMM implements some functionality using compiler-intrinsics and multiple code-paths which are scheduled according to CPUID. In contrast to <code>INTRINSICS=2</code> (default), <code>INTRINSICS=1</code> enables a fully static code path according to the desired target. If no target is given (e.g., <code>AVX=3</code>, or <code>AVX=2</code>), instruction set extensions cannot be leveraged for such code-paths. Try to fix failing compilation by building the latest GNU Binutils (and <code>export PATH=/path/to/binutils/bin:${PATH}</code>). Binutils are versioned independently of <span>GNU GCC</span> and other compilers. If one cannot update Binutils, work around with a CPUID-value as tabulated in <a href="https://github.com/libxsmm/libxsmm/blob/main/include/libxsmm_cpuid.h">libxsmm_cpuid.h</a>: start at the upper end (less than 1999) and decrement until compilation passes (make INTRINSICS=<em>CPUID</em>, e.g., <code>make INTRINSICS=1021</code>). As a last resort, rely on a fully static code path:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make INTRINSICS=1"><pre>make INTRINSICS=1</pre></div> <p dir="auto">To test and validate a build, please consult <a href="https://github.com/libxsmm/libxsmm/wiki/Validation">https://github.com/libxsmm/libxsmm/wiki/Validation</a>. To run some basic sanity checks, remember that each set of given key-value pairs represents a different build (and test):</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make STATIC=0 tests"><pre>make STATIC=0 tests</pre></div> <p dir="auto">To remove intermediate files, or to remove all generated files and folders (including the interface and the library archives), run one of the make-targets below. An additional distclean-target recursively cleans the entire tree (after <span>version 1.9</span>).</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make clean make realclean"><pre>make clean make realclean</pre></div> <p dir="auto"><a name="user-content-fortran"></a>FORTRAN code can make use of LIBXSMM:</p> <ul dir="auto"> <li>By using the module and linking with <code>libxsmmf</code>, <code>libxsmm</code>, and <code>libxsmmext</code>,</li> <li><a name="user-content-header-only-fortran"></a>By including <code>libxsmm.f</code> and linking with <code>libxsmm</code>, and <code>libxsmmext</code>, or</li> <li>By (implicitly) calling a SUBROUTINE and linking with <code>libxsmm</code>, and <code>libxsmmext</code>.</li> </ul> <p dir="auto"><strong>Note</strong>: <code>libxsmmf</code> requires <code>libxsmmext</code> (starting with LIBXSMM 2.0), and thereby requires to link with the OpenMP runtime as well.</p> <p dir="auto">Using the Fortran module (or including the interface), requires at least a <span>Fortran 2003</span> compiler (F2K3). <span>FORTRAN 77</span> compatibility is only implicitly available (no interface), and the available subset of routines is documented in <code>libxsmm.f</code> and marked with <a href="https://github.com/libxsmm/libxsmm/search?q=implementation+provided+for+Fortran+77+compatibility">comments</a> (part of the implementation).</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Header-Only</h3><a id="user-content-header-only" class="anchor" aria-label="Permalink: Header-Only" href="#header-only"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><span>Version 1.4.4</span> introduced support for "header-only" usage in C and C++. By only including <code>libxsmm_source.h</code> allows to get around building the library. However, this gives up on a clearly defined application binary interface (ABI). An ABI may allow for hot-fixes after deploying an application (when relying on the shared library form), and it may also ensure to only rely on the public interface of LIBXSMM. In contrast, the header-only form not only exposes the internal implementation of LIBXSMM but can also increase the turnaround time during development of an application (due to longer compilation times). The header file is intentionally named "libxsmm_<strong>source</strong>.h" since this header file relies on the <a href="https://github.com/libxsmm/libxsmm/tree/main/src">src</a> directory (with the implications as noted earlier).</p> <p dir="auto"><a name="user-content-zero-config"></a>The header-only form depends on <code>libxsmm_source.h</code> which is <em>generated</em> according to the content of the source folder (<code>src</code>). <span>LIBXSMM 1.16</span> (and later) provides header-only support without invoking a make-target (zero configuration) for any given checkout of LIBXSMM. To use configured header-only (non-default), LIBXSMM_CONFIGURED must be defined (<code>-D</code>). Previously, it was necessary to invoke <code>make header-only</code> (v1.6.2 or later), <code>make cheader</code> (prior to v1.6.2), or any target building the library (<code>make</code>). The zero-config feature allows 3rd-party build systems an easier integration of LIBXSMM, which also holds true if the system builds LIBXSMM from source (see <a href="#zero-config-abi">classic ABI</a>). Fortran code may <a href="#header-only-fortran">include</a> <code>libxsmm.f</code> but still requires that interface to be generated.</p> <p dir="auto"><strong>Note</strong>: building an application applies the same build settings to LIBXSMM! For instance, to omit debug code inside of LIBXSMM <code>NDEBUG</code> must be defined (<code>-DNDEBUG</code>).</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Rules for building LIBXSMM</h2><a id="user-content-rules-for-building-libxsmm" class="anchor" aria-label="Permalink: Rules for building LIBXSMM" href="#rules-for-building-libxsmm"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">LIBXSMM can be used as header-only library, i.e., no source code must be (pre-)built. However, it can be desirable to build LIBXSMM as an intermediate library using a custom setup or build system. The latter can still implement custom build rules to configure LIBXSMM's interface before building the code. More likely, building LIBXSMM from source in a custom fashion can still be omitting to configure the interface and rely on "(zero-config)[#zero-config-abi]", i.e., defining LIBXSMM_DEFAULT_CONFIG (<code>-DLIBXSMM_DEFAULT_CONFIG</code>). For example, a CMake module for LIBXSMM can look like:</p> <div class="highlight highlight-source-cmake notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="include(FetchContent) FetchContent_Declare( xsmm URL https://github.com/chelini/libxsmm/archive/<your-preferred-revision>.tar.gz URL_HASH SHA256=<sha256sum-corresponding-to-above-revision> ) FetchContent_GetProperties(xsmm) if(NOT xsmm_POPULATED) FetchContent_Populate(xsmm) endif() set(LIBXSMMROOT ${xsmm_SOURCE_DIR}) file(GLOB _GLOB_XSMM_SRCS LIST_DIRECTORIES false CONFIGURE_DEPENDS ${LIBXSMMROOT}/src/*.c) list(REMOVE_ITEM _GLOB_XSMM_SRCS ${LIBXSMMROOT}/src/libxsmm_generator_gemm_driver.c) set(XSMM_INCLUDE_DIRS ${LIBXSMMROOT}/include) add_library(xsmm STATIC ${_GLOB_XSMM_SRCS}) target_include_directories(xsmm PUBLIC ${XSMM_INCLUDE_DIRS}) target_compile_definitions(xsmm PUBLIC LIBXSMM_DEFAULT_CONFIG ) target_compile_definitions(xsmm PRIVATE __BLAS=0 )"><pre><span class="pl-k">include</span>(FetchContent) FetchContent_Declare( xsmm URL https://github.com/chelini/libxsmm/archive/<your-preferred-revision>.tar.gz URL_HASH SHA256=<sha256sum-corresponding-to-above-revision> ) FetchContent_GetProperties(xsmm) <span class="pl-k">if</span>(<span class="pl-k">NOT</span> xsmm_POPULATED) FetchContent_Populate(xsmm) <span class="pl-k">endif</span>() <span class="pl-k">set</span>(LIBXSMMROOT <span class="pl-k">${xsmm_SOURCE_DIR}</span>) <span class="pl-k">file</span>(GLOB _GLOB_XSMM_SRCS LIST_DIRECTORIES <span class="pl-k">false</span> CONFIGURE_DEPENDS <span class="pl-k">${LIBXSMMROOT}</span>/src/*.c) <span class="pl-k">list</span>(REMOVE_ITEM _GLOB_XSMM_SRCS <span class="pl-k">${LIBXSMMROOT}</span>/src/libxsmm_generator_gemm_driver.c) <span class="pl-k">set</span>(XSMM_INCLUDE_DIRS <span class="pl-k">${LIBXSMMROOT}</span>/<span class="pl-e">include</span>) <span class="pl-k">add_library</span>(xsmm <span class="pl-e">STATIC</span> <span class="pl-k">${_GLOB_XSMM_SRCS}</span>) <span class="pl-k">target_include_directories</span>(xsmm <span class="pl-e">PUBLIC</span> <span class="pl-k">${XSMM_INCLUDE_DIRS}</span>) <span class="pl-k">target_compile_definitions</span>(xsmm <span class="pl-e">PUBLIC</span> LIBXSMM_DEFAULT_CONFIG ) <span class="pl-k">target_compile_definitions</span>(xsmm <span class="pl-e">PRIVATE</span> __BLAS=0 )</pre></div> <p dir="auto">Above, LIBXSMM_DEFAULT_CONFIG is propagated to dependent code (<code>PUBLIC</code>) and further, LIBXSMM is configured to not require a LAPACK/BLAS library/fallback (<code>-D__BLAS=0</code>).</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Link Instructions</h2><a id="user-content-link-instructions" class="anchor" aria-label="Permalink: Link Instructions" href="#link-instructions"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">Using the <a href="#classic-library-abi">classic ABI</a> (including <a href="#fortran">Fortran</a> code), requires linking LIBXSMM against the application. The library is agnostic with respect to the threading-runtime, and therefore an application is free to use any threading runtime (e.g., OpenMP). The library is also thread-safe, and multiple application threads can call LIBXSMM's routines concurrently. Enabling OpenMP for LIBXSMM's main library is supported as well (OMP=1), and mostly affects the synchronization primitives used inside of the library. All the "omp" functionality (function postfix) is served by the <code>libxsmmext</code> library, which is automatically built with OpenMP enabled. When using this "omp" functionality, <code>libxsmmext</code> needs to be present at the link line.</p> <markdown-accessiblity-table><table> <thead> <tr> <th align="left"><a name="user-content-table-of-libraries"></a>Library</th> <th>Purpose</th> </tr> </thead> <tbody> <tr> <td align="left">libxsmm</td> <td>Thread-safe core functions (same routine can be called concurrently). Contains routines that can take a thread-ID and the number of library-external threads.</td> </tr> <tr> <td align="left">libxsmmf</td> <td>Necessary when using the Fortran MODule but not when including <code>libxsmm.f</code> or relying on implicit interfaces (<a href="https://github.com/libxsmm/libxsmm/search?q=implementation+provided+for+Fortran+77+compatibility">Fortran 77</a>).</td> </tr> <tr> <td align="left">libxsmmext</td> <td>Provides library-internal OpenMP-threaded functions carrying the <code>omp</code> postfix when compared to function name names of the core library.</td> </tr> <tr> <td align="left">libxsmmnoblas</td> <td>Supplies faked symbols for <code>dgemm</code> (and others) and thereby removes the need to link against a LAPACK/BLAS library.</td> </tr> </tbody> </table></markdown-accessiblity-table> <p dir="auto"><a name="user-content-pkg-config"></a>To ease linking with LIBXSMM, <code>pkg-config</code> can be used. For example:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="export PKG_CONFIG_PATH=/path/to/libxsmm/lib pkg-config libxsmm --libs"><pre><span class="pl-k">export</span> PKG_CONFIG_PATH=/path/to/libxsmm/lib pkg-config libxsmm --libs</pre></div> <p dir="auto">Similarly, an application is free to choose any BLAS or LAPACK library (if the link model available on the OS supports this), and therefore linking GEMM routines when linking LIBXSMM itself (by supplying BLAS=1|2) may prevent a user from making this decision at the time of linking the actual application. To use LIBXSMM without GEMM-related functionality, any BLAS-dependency can be removed in two ways: <span>(1) building</span> a special library with <code>make BLAS=0</code>, or <span>(2) linking</span> the application against the <code>libxsmmnoblas</code> library. If an application however uses BLAS already, the <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#call-wrapper">Call Wrapper</a> can be used to intercept existing BLAS calls (and to rely on LIBXSMM instead).</p> <p dir="auto"><strong>Note</strong>: LIBXSMM does not support to dynamically link <code>libxsmm</code> or <code>libxsmmext</code> ("so") when BLAS is linked statically ("a"). If BLAS is linked statically, the static version of LIBXSMM must be used!</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Installation</h3><a id="user-content-installation" class="anchor" aria-label="Permalink: Installation" href="#installation"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">There are two main mechanisms to install LIBXSMM (both mechanisms can be combined): <span>(1) building</span> the library in an <span>out‑of‑tree</span> fashion, and <span>(2) installing</span> into a certain location. <a name="user-content-install-build"></a>Building in an <span>out‑of‑tree</span> fashion looks like:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="cd libxsmm-install make -f /path/to/libxsmm/Makefile"><pre><span class="pl-c1">cd</span> libxsmm-install make -f /path/to/libxsmm/Makefile</pre></div> <p dir="auto"><a name="user-content-install-prefix"></a>Installation into a specific location looks like (<code>PREFIX</code> or <code>DESTDIR</code>):</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make MNK="1 2 3 4 5" PREFIX=/path/to/libxsmm-install install"><pre>make MNK=<span class="pl-s"><span class="pl-pds">"</span>1 2 3 4 5<span class="pl-pds">"</span></span> PREFIX=/path/to/libxsmm-install install</pre></div> <p dir="auto"><a name="user-content-install-destdir"></a>Both <code>PREFIX</code> and <code>DESTDIR</code> are equivalent and can be relative or absolute paths. An installation can be repeated for different locations without triggering a rebuild. The prefix directory <em>inside</em> of each of the <a href="#pkg-config">package configuration files</a> is set to where LIBXSMM is built (staging folder) unless <code>PREFIX</code> or <code>DESTDIR</code> is specified. The effect of <code>PREFIX</code> (or <code>DESTDIR</code>) with respect to the pkg-config files is independent of whether the install-target is invoked or not (make).</p> <p dir="auto">Further, performing <code>make install-minimal</code> omits the documentation (default: <code>PREFIX/share/libxsmm</code>). Moreover, PINCDIR, POUTDIR, PBINDIR, and PDOCDIR allow to customize the locations underneath of the PREFIX location. To build a general package for an unpredictable audience (Linux distribution, or similar), it is advised to not over-specify or customize the build step, i.e., JIT, SSE, AVX, OMP, BLAS, etc. should not be used. The following is building and installing a complete set of libraries where the generated interface matches both the static and the shared libraries:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make PREFIX=/path/to/libxsmm-install STATIC=0 install make PREFIX=/path/to/libxsmm-install install"><pre>make PREFIX=/path/to/libxsmm-install STATIC=0 install make PREFIX=/path/to/libxsmm-install install</pre></div> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Runtime Control<a name="user-content-running"></a></h2><a id="user-content-runtime-control" class="anchor" aria-label="Permalink: Runtime Control" href="#runtime-control"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Handling Errors</h3><a id="user-content-handling-errors" class="anchor" aria-label="Permalink: Handling Errors" href="#handling-errors"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">The library handles errors with mechanisms available to the C programming language (no exceptions). The backend uses result codes passed by an argument rather than an actual return value. Such an argument is often a descriptor (struct) guiding and covering the state of the code generation. The frontend however may not hand-out any error state, which can be a big relief on the call-side. Instead, the frontend implements a <a href="#verbose-mode">verbose mode</a> to inform about unexpected input or an error captured from the backend. Guiding principles of LIBXSMM are muted operation by default (non-verbose) and no unexpected exit from execution.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Verbose Mode</h3><a id="user-content-verbose-mode" class="anchor" aria-label="Permalink: Verbose Mode" href="#verbose-mode"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">The <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_aux.md#getting-and-setting-the-verbosity">verbose mode</a> (level of verbosity) allows for an insight into the code dispatch mechanism by receiving a small, tabulated statistic as soon as the library terminates. The design point for this functionality is to not impact the performance of any critical code path, i.e., verbose mode is always enabled and does not require symbols (SYM=1) or debug code (DBG=1). The statistics appears (<code>stderr</code>) when the environment variable LIBXSMM_VERBOSE is set to a non-zero value. For example:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="LIBXSMM_VERBOSE=1 ./myapplication [... application output] HSW/SP TRY JIT STA COL 0..13 0 0 0 0 14..23 0 0 0 0 24..128 3 3 0 0"><pre>LIBXSMM_VERBOSE=1 ./myapplication [... application output] HSW/SP TRY JIT STA COL 0..13 0 0 0 0 14..23 0 0 0 0 24..128 3 3 0 0</pre></div> <p dir="auto">The tables are distinct between single-precision and double-precision, but either table is pruned if all counters are zero. If both tables are pruned, the library shows the code path which would have been used for JIT'ting the code: <code>LIBXSMM_TARGET=hsw</code> (otherwise the code path is shown in the table's header). The actual counters are collected for three buckets: small kernels (<span>MNK<sup>1/3</sup> <= 13</span>), medium-sized kernels (<span>13 < MNK<sup>1/3</sup> <= 23</span>), and larger kernels (<span>23 < MNK<sup>1/3</sup> <= 64</span>; the actual upper bound depends on LIBXSMM_MAX_MNK as selected at compile-time). Keep in mind, that "larger" is supposedly still small in terms of arithmetic intensity (which grows linearly with the kernel size). Unfortunately, the arithmetic intensity depends on the way a kernel is used (which operands are loaded/stored into main memory), and it is not performance-neutral to collect this information.</p> <p dir="auto">The TRY counter represents all attempts to register statically generated kernels, and all attempts to dynamically generate and register kernels. The TRY counter includes rejected JIT requests due to unsupported GEMM arguments. The JIT and STA counters distinct the successful cases of the afore mentioned event (TRY) into dynamically (JIT) and statically (STA) generated code. In case the capacity (<span>O(<em>n</em>) = 10<sup>5</sup></span>) of the code registry is exhausted, no more kernels can be registered although further attempts are not prevented. Registering many kernels (<span>O(<em>n</em>) = 10<sup>3</sup></span>) may ramp the number of hash key collisions (COL), which can degrade performance. The latter is prevented if the small thread-local cache is utilized effectively.</p> <p dir="auto">Since explicitly JIT-generated code (<code>libxsmm_?mmdispatch</code>) does not fall under the THRESHOLD criterion, the above table is extended by one line if large kernels have been requested. This indicates a missing threshold-criterion (customized dispatch) or asks for cache-blocking the matrix multiplication. Setting a verbosity level of at least two summarizes the number of registered JIT-generated kernels, which includes the total size and counters for GEMM, MCOPY (matrix copy), and TCOPY (matrix transpose) kernels.</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="Registry: 20 MB (gemm=0 mcopy=14 tcopy=0)"><pre>Registry: 20 MB (gemm=0 mcopy=14 tcopy=0)</pre></div> <p dir="auto">If the call-wrapper is used, an additional runtime statistic becomes available (see <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_mm.md#call-wrapper">Call Wrapper</a>).</p> <p dir="auto"><a name="user-content-objdump"></a><strong>Note</strong>: Setting LIBXSMM_VERBOSE to a negative value dumps each generated JIT kernel to a file (binary) with each file being named like the function name shown in <a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_prof.md#intelvtuneamplifier">Intel VTune</a>. Disassembly of the raw binary files can be accomplished by:</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="objdump -D -b binary -m i386 -M x86-64 [JIT-dump-file]"><pre>objdump -D -b binary -m i386 -M x86-64 [JIT-dump-file]</pre></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Call Trace</h3><a id="user-content-call-trace" class="anchor" aria-label="Permalink: Call Trace" href="#call-trace"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">During the initial steps of employing the LIBXSMM API, one may rely on a debug version of the library (<code>make DBG=1</code>). The latter also implies console output (<code>stderr</code>) in case of an error/warning condition inside of the library. It is also possible to print the execution flow (call trace) inside of LIBXSMM (can be combined with DBG=1 or OPT=0):</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="make TRACE=1"><pre>make TRACE=1</pre></div> <p dir="auto">Building an application which traces calls (inside of the library) requires the shared library of LIBXSMM, alternatively the application is required to link the static library of LIBXSMM in a dynamic fashion (GNU tool chain: <code>-rdynamic</code>). Tracing calls (without debugger) can be then accomplished by an environment variable called LIBXSMM_TRACE.</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="LIBXSMM_TRACE=1 ./myapplication"><pre>LIBXSMM_TRACE=1 ./myapplication</pre></div> <p dir="auto">Syntactically up to three arguments separated by commas (which allows to omit arguments) are taken (<em>tid</em>,<em>i</em>,<em>n</em>): <em>tid</em> signifies the ID of the thread to be traced with 1...NTHREADS being valid and where LIBXSMM_TRACE=1 is filtering for the "main thread" (in fact the first thread running into the trace facility); grabbing all threads (no filter) can be achieved by supplying a negative id (which is also the default when omitted). The second argument is pruning higher levels of the call-tree with <em>i=1</em> being the default (level zero is the highest at the same level as the main function). The last argument is taking the number of inclusive call levels with <em>n=-1</em> being the default (signifying no filter).</p> <p dir="auto">Although the <code>ltrace</code> (Linux utility) provides similar insight, the trace facility might be useful due to the afore mentioned filtering expressions. Please note that the trace facility is severely impacting the performance (even with LIBXSMM_TRACE=0), and this is not just because of console output but rather since inlining (internal) functions might be prevented along with additional call overhead on each function entry and exit. Therefore, debug symbols can be also enabled separately (<code>make SYM=1</code>; implied by TRACE=1 or DBG=1) which might be useful when profiling an application.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Verification</h3><a id="user-content-verification" class="anchor" aria-label="Permalink: Verification" href="#verification"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto">This section refers to testing correctness of an application using LIBXSMM utilities, i.e., using <code>libxsmm_matdiff</code> or <code>libxsmm_matdiff_epsilon</code> in particular. The former function (<code>libxsmm_matdiff</code>) compares two matrices (which can degenerate to vector shape), and yields a structure with information about the difference of both matrices (gold vs. test). The latter function (<code>libxsmm_matdiff_epsilon</code>) combines absolute and relative norms (given by afore mentioned structure) and calculates a scalar "epsilon" which can be used to check against a margin.</p> <p dir="auto">Using <code>libxsmm_matdiff_epsilon</code> in an application exposes an environment variable <code>LIBXSMM_MATDIFF</code> which can specify a file or directory path (<code>LIBXSMM_MATDIFF=1</code> simply uses some filename as default). In any case, the application appends one line to the respective file for each call of <code>libxsmm_matdiff_epsilon</code>. A data record consists of the epsilon and the command line used to launch the application. A generated file can be further evaluated, e.g., <code>sort -gk1 libxsmm_matdiff.log | tail -n 10</code> which yields the largest ten epsilon values discovered along with the application's command line.</p> <p dir="auto">The environment variable <code>LIBXSMM_MATDIFF</code> can carry optional space-separated arguments to amend each file entry like <code>export LIBXSMM_MATDIFF="libxsmm_matdiff.log hello world"</code>. In sophisticated cases this can be used to amend a value only known at runtime, e.g., the actual margin which is used to judge the epsilon (<code>putenv</code>).</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Performance</h2><a id="user-content-performance" class="anchor" aria-label="Permalink: Performance" href="#performance"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><a name="user-content-profiling"></a>Profiling an application, which uses LIBXSMM's JIT-code is well-supported. The library supports <span>Intel VTune Amplifier</span> and <span>Linux perf</span>. Details are given on how to include profiler support, and how to run the application.</p> <ul dir="auto"> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_prof.md#intelvtuneamplifier">Profiling using Intel VTune Amplifier</a></li> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_prof.md#linuxperf">Profiling using Linux perf</a></li> </ul> <p dir="auto"><a name="user-content-tuning"></a>At build time, a variety of options exist to customize LIBXSMM. The library is setup for a broad range of use cases, which include sophisticated defaults for typical use.</p> <ul dir="auto"> <li><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_tune.md#tuning">Customizing performance</a></li> <li><a name="user-content-auto-dispatch"></a><a href="/libxsmm/libxsmm/blob/main/documentation/libxsmm_tune.md#auto-dispatch">Tuning auto-dispatch</a></li> </ul> <p dir="auto"><a name="user-content-results"></a>To find performance results of applications or performance reproducers, the repository provides an orphaned branch called "results" which collects collateral material such as measured performance results along with explanatory figures. The results can be found at <a href="https://github.com/libxsmm/libxsmm/tree/results#libxsmm-results">https://github.com/libxsmm/libxsmm/tree/results#libxsmm-results</a>, or the results can be cloned as shown below.</p> <div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="git clone --branch results \ https://github.com/libxsmm/libxsmm.git \ libxsmm-results"><pre>git clone --branch results \ https://github.com/libxsmm/libxsmm.git \ libxsmm-results</pre></div> <p dir="auto">Please note that comparing performance results depends on whether the operands of the matrix multiplication are streamed or not. For example, multiplying with all matrices covered by the L1 cache may have an emphasis towards an implementation which perhaps performs worse for the real workload (if this real workload needs to stream some or all matrices from the main memory). Most of the <a href="https://github.com/libxsmm/libxsmm/tree/main/samples">code samples</a> are aimed to reproduce performance results, and it is encouraged to model the exact case or to look at real <a href="#applications">applications</a>.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Applications</h2><a id="user-content-applications" class="anchor" aria-label="Permalink: Applications" href="#applications"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">High Performance Computing (HPC)</h3><a id="user-content-high-performance-computing-hpc" class="anchor" aria-label="Permalink: High Performance Computing (HPC)" href="#high-performance-computing-hpc"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><b>[1] </b><a href="https://cp2k.org/" rel="nofollow">https://cp2k.org/</a>: Open Source Molecular Dynamics and the <a href="https://github.com/cp2k/dbcsr">DBCSR library</a>, which processes batches of small matrix multiplications. The batches originate from a distributed block-sparse matrix with problem-specific small matrices. Starting with <a href="https://www.cp2k.org/version_history" rel="nofollow">CP2K 3.0</a>, LIBXSMM can substitute CP2K's <code>libsmm</code> library.</p> <p dir="auto"><b>[2] </b><a href="https://github.com/SeisSol/SeisSol/">https://github.com/SeisSol/SeisSol/</a>: SeisSol is one of the leading codes for earthquake scenarios, for simulating dynamic rupture processes. LIBXSMM provides highly optimized assembly kernels which form the computational back-bone of SeisSol (see <a href="https://github.com/TUM-I5/seissol_kernels/">https://github.com/TUM-I5/seissol_kernels/</a>.</p> <p dir="auto"><b>[3] </b><a href="https://github.com/NekBox/NekBox">https://github.com/NekBox/NekBox</a>: NekBox is a highly scalable and portable spectral element code, which is inspired by the <a href="https://nek5000.mcs.anl.gov/" rel="nofollow">Nek5000</a> code. NekBox is specialized for box geometries and intended to prototype new methods as well as to leverage FORTRAN beyond the FORTRAN 77 standard. LIBXSMM can be used to substitute the <a href="https://github.com/Nek5000/NekBox/blob/box/mxm_std.F90">MXM_STD</a> code. Please also note LIBXSMM's <a href="https://github.com/libxsmm/libxsmm/tree/main/samples/nek#nek-sample-collection">NekBox reproducer</a>.</p> <p dir="auto"><b>[4] </b><a href="https://github.com/Nek5000/Nek5000">https://github.com/Nek5000/Nek5000</a>: Nek5000 is the open-source, highly-scalable, always-portable spectral element code from <a href="https://nek5000.mcs.anl.gov/" rel="nofollow">https://nek5000.mcs.anl.gov/</a>. The development branch of the Nek5000 code <a href="https://github.com/Nek5000/Nek5000/blob/master/core/mxm_wrapper.f">incorporates</a> LIBXSMM.</p> <p dir="auto"><b>[5] </b><a href="http://pyfr.org/" rel="nofollow">http://pyfr.org/</a>: PyFR is an open-source Python based framework for solving advection-diffusion type problems on streaming architectures by using the flux reconstruction approach. PyFR 1.6.0 optionally <a href="http://pyfr.org/user_guide.php" rel="nofollow">incorporates LIBXSMM</a> as a matrix multiplication provider for the OpenMP backend. Please also note LIBXSMM's <a href="https://github.com/libxsmm/libxsmm/tree/main/samples/pyfr">PyFR-related code sample</a>.</p> <p dir="auto"><b>[6] </b><a href="http://dial3343.org/about/" rel="nofollow">http://dial3343.org/about/</a>: The Extreme-scale Discontinuous Galerkin Environment (EDGE) is a solver for hyperbolic partial differential equations with emphasis on seismic simulations. The EDGE <a href="https://github.com/3343/edge">source code</a> optionally relies on LIBXSMM, but for high performance LIBXSMM's kernels are highly recommended.</p> <p dir="auto"><b>[7] </b><a href="https://sxs-collaboration.github.io/spectre/" rel="nofollow">https://sxs-collaboration.github.io/spectre/</a>: SpECTRE is an open-source code for multi-scale, multi-physics problems in astrophysics and gravitational physics which runs at Petascale and is designed for Exascale computers. In the future, SpECTRE may be applied to problems across discipline boundaries in fluid dynamics, geoscience, plasma physics, nuclear physics, and engineering.</p> <p dir="auto"><b>[8] </b><a href="https://ceed.exascaleproject.org/ceed-code/" rel="nofollow">https://ceed.exascaleproject.org/ceed-code/</a>: The Center for Efficient Exascale Discretizations (CEED) is building on the efforts of the Nek5000, MFEM, MAGMA, OCCA and PETSc projects to develop application program interfaces (APIs), both at high-level and at low-level to enable applications to take advantage of high-order methods. The CEED low-level API, <a href="https://ceed.exascaleproject.org/libceed/" rel="nofollow">libCEED</a> uses LIBXSMM as a <a href="https://github.com/CEED/libCEED#backends">backend</a> for high performance on CPUs.</p> <p dir="auto"><b>[9] </b><a href="https://github.com/romeric/Fastor">https://github.com/romeric/Fastor</a>: Fastor is a lightweight high performance tensor algebra framework for modern C++ and can optionally use LIBXSMM as <a href="https://github.com/romeric/Fastor/wiki/9.-Using-the-LIBXSMM-MKL-JIT-backend">JIT-backend</a>.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Machine Learning (ML)</h3><a id="user-content-machine-learning-ml" class="anchor" aria-label="Permalink: Machine Learning (ML)" href="#machine-learning-ml"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><b>[10] </b><a href="https://github.com/plaidml/plaidml">https://github.com/plaidml/plaidml</a>: PlaidML is an open source tensor compiler aiming for performance portability across a wide range of CPUs, GPUs and other accelerators. Combined with Intel’s nGraph compiler, PlaidML is targeting popular deep learning frameworks such as PyTorch, Keras (TensorFlow), and OpenVino. <a href="https://github.com/plaidml/plaidml/tree/plaidml-v1">PlaidML/v1</a> (development branch) adopted <a href="https://mlir.llvm.org/" rel="nofollow">MLIR</a>, an extensible compiler infrastructure gaining industry-wide adoption. PlaidML/v1 started using LIBXSMM as backend for targeting CPUs.</p> <p dir="auto"><b>[11] </b><a href="https://github.com/intel/intel-extension-for-pytorch">https://github.com/intel/intel-extension-for-pytorch</a>: Intel Extension for PyTorch aims for a smooth user experience of PyTorch on CPUs by the means of good performance. The extension pack started to rely on <a href="https://arxiv.org/abs/2005.04680" rel="nofollow">LIBXSMM for achieving high performance on CPUs</a>.</p> <p dir="auto"><b>[12] </b><a href="https://github.com/libxsmm/tpp-pytorch-extension">https://github.com/libxsmm/tpp-pytorch-extension</a>: Intel(R) Tensor Processing Primitive Extension for pytorch is an open source software library the integrates Tensor Processing Primitives (<a href="https://arxiv.org/abs/2104.05755" rel="nofollow">TPP</a>) into pytorch. It is aiming for a smooth user experience of PyTorch on CPUs by the means of good performance. Intel's MLPerf Training submission codes leverage this <a href="https://github.com/mlcommons/training_results.1/tree/main/Intel/benchmarks/bert/implementations/pytorch-cpu">project</a>.</p> <p dir="auto"><b>[13] </b><a href="https://github.com/libxsmm/libxsmm-dnn">https://github.com/libxsmm/libxsmm-dnn</a>: LIBXSMM-DNN is an open source software library that demonstrates how Tensor Processing Primitives (<a href="https://arxiv.org/abs/2104.05755" rel="nofollow">TPP</a>) can be used to implement various deep learning primitives such as convolutions, linear layers or even pooling and norming. Due to the use of TPP not a single line of platform-specific code is needed.</p> <div class="markdown-heading" dir="auto"><h3 tabindex="-1" class="heading-element" dir="auto">Automated Driving (AD)</h3><a id="user-content-automated-driving-ad" class="anchor" aria-label="Permalink: Automated Driving (AD)" href="#automated-driving-ad"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><b>[15] </b><a href="https://software.seek.intel.com/accelerating-eigen-math-library" rel="nofollow">https://software.seek.intel.com/accelerating-eigen-math-library</a>: Accelerating The Eigen Math Library for Automated Driving Workloads: The Need for Speed in Kalman Filtering. An article in <a href="https://software.intel.com/content/www/us/en/develop/download/parallel-universe-magazine-issue-31-january-2018.html" rel="nofollow">Issue 31</a> of The Parallel Universe magazine (<a href="https://software.intel.com/content/dam/develop/public/us/en/documents/parallel-universe-issue-31.pdf" rel="nofollow">pdf</a>).</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">References</h2><a id="user-content-references" class="anchor" aria-label="Permalink: References" href="#references"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><b>[1] </b><a href="https://sc19.supercomputing.org/proceedings/tech_poster/tech_poster_pages/rpost244.html" rel="nofollow">https://sc19.supercomputing.org/proceedings/tech_poster/tech_poster_pages/rpost244.html</a>: High-Performance Deep Learning via a Single Building Block (<a href="https://sc19.supercomputing.org/proceedings/tech_poster/poster_files/rpost244s2-file2.pdf" rel="nofollow">poster</a> and <a href="https://sc19.supercomputing.org/proceedings/tech_poster/poster_files/rpost244s2-file3.pdf" rel="nofollow">abstract</a>), SC’19: The International Conference for High Performance Computing, Networking, Storage, and Analysis, Denver (Colorado).</p> <p dir="auto"><b>[2] </b><a href="https://dl.acm.org/doi/10.1109/SC.2018.00069" rel="nofollow">https://dl.acm.org/doi/10.1109/SC.2018.00069</a>: Anatomy of High-Performance Deep Learning Convolutions on SIMD Architectures (<a href="https://arxiv.org/pdf/1808.05567.pdf" rel="nofollow">paper</a>). SC'18: The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas (Texas).</p> <p dir="auto"><b>[3] </b><a href="https://pasc17.pasc-conference.org/fileadmin/user_upload/pasc17/program/post116s2.pdf" rel="nofollow">https://pasc17.pasc-conference.org/fileadmin/user_upload/pasc17/program/post116s2.pdf</a>: DBCSR: A Sparse Matrix Multiplication Library for Electronic Structure Codes (poster), PASC’17: The PASC17 Conference, Lugano (Switzerland).</p> <p dir="auto"><b>[4] </b><a href="https://sc17.supercomputing.org/SC17%20Archive/tech_poster/tech_poster_pages/post190.html" rel="nofollow">https://sc17.supercomputing.org/SC17%20Archive/tech_poster/tech_poster_pages/post190.html</a>: Understanding the Performance of Small Convolution Operations for CNN on Intel Architecture (<a href="https://sc17.supercomputing.org/SC17%20Archive/tech_poster/poster_files/post190s2-file2.pdf" rel="nofollow">poster</a> and <a href="https://sc17.supercomputing.org/SC17%20Archive/tech_poster/poster_files/post190s2-file3.pdf" rel="nofollow">abstract</a>), SC’17: The International Conference for High Performance Computing, Networking, Storage, and Analysis, Denver (Colorado).</p> <p dir="auto"><b>[5] </b><a href="https://www.computer.org/csdl/proceedings-article/sc/2016/8815a981/12OmNCeaQ1D" rel="nofollow">https://www.computer.org/csdl/proceedings-article/sc/2016/8815a981/12OmNCeaQ1D</a>: LIBXSMM: Accelerating Small Matrix Multiplications by Runtime Code Generation. SC'16: The International Conference for High Performance Computing, Networking, Storage and Analysis, Salt Lake City (Utah).</p> <p dir="auto"><b>[6] </b><a href="http://sc15.supercomputing.org/sites/all/themes/SC15images/tech_poster/tech_poster_pages/post137.html" rel="nofollow">http://sc15.supercomputing.org/sites/all/themes/SC15images/tech_poster/tech_poster_pages/post137.html</a>: LIBXSMM: A High Performance Library for Small Matrix Multiplications (<a href="http://sc15.supercomputing.org/sites/all/themes/SC15images/tech_poster/poster_files/post137s2-file2.pdf" rel="nofollow">poster</a> and <a href="http://sc15.supercomputing.org/sites/all/themes/SC15images/tech_poster/poster_files/post137s2-file3.pdf" rel="nofollow">abstract</a>). SC'15: The International Conference for High Performance Computing, Networking, Storage and Analysis, Austin (Texas).</p> <p dir="auto"><b>[7] </b><a href="https://arxiv.org/abs/2104.05755" rel="nofollow">Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning & HPC Workloads</a> SC'21: The International Conference for High Performance Computing, Networking, Storage and Analysis, St Louis.</p> <div class="markdown-heading" dir="auto"><h2 tabindex="-1" class="heading-element" dir="auto">Articles</h2><a id="user-content-articles" class="anchor" aria-label="Permalink: Articles" href="#articles"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path></svg></a></div> <p dir="auto"><b>[1] </b><a href="https://www.nextplatform.com/2019/10/09/cloudy-supercomputers-join-the-hpc-petascale-club/" rel="nofollow">https://www.nextplatform.com/2019/10/09/cloudy-supercomputers-join-the-hpc-petascale-club/</a>: Cloudy Supercomputers Join the HPC Petascale Club. An article written by Rob Farber, 2019. The article covers LIBXSMM in a separate section.</p> <p dir="auto"><b>[2] </b><a href="https://www.nextplatform.com/2019/06/26/counting-the-cost-of-scaling-hpc-applications/" rel="nofollow">https://www.nextplatform.com/2019/06/26/counting-the-cost-of-scaling-hpc-applications/</a>: Counting The Cost Of Scaling HPC Applications. An article written by Timothy Prickett Morgan, 2019. This article is about CP2K Open Source Molecular Dynamics and not about LIBXSMM. However, LIBXSMM was key for application performance.</p> <p dir="auto"><b>[3] </b><a href="https://www.nextplatform.com/2019/06/26/counting-the-cost-of-scaling-hpc-applications/" rel="nofollow">https://www.nextplatform.com/2019/06/26/counting-the-cost-of-scaling-hpc-applications/</a>: Azure Benchmarks HC-series Across Twenty-thousand Cores for HPC. An article written by John Russell, 2019. This article is about CP2K Open Source Molecular Dynamics and not about LIBXSMM. However, LIBXSMM was key for application performance.</p> <p dir="auto"><b>[4] </b><a href="https://software.intel.com/content/www/us/en/develop/download/parallel-universe-magazine-issue-34-october-2018.html" rel="nofollow">https://software.intel.com/sites/default/files/parallel-universe-issue-34.pdf</a>: LIBXSMM: An Open Source-Based Inspiration for Hardware and Software Development at Intel (<a href="https://software.intel.com/content/dam/develop/public/us/en/documents/parallel-universe-issue-34.pdf" rel="nofollow">pdf</a>). An article written by Hans Pabst, Greg Henry, and Alexander Heinecke, 2018.</p> <p dir="auto"><b>[5] </b><a href="https://medium.com/@rmfarber/libxsmm-brings-deep-learning-lessons-learned-to-many-hpc-applications-9143c6c93125" rel="nofollow">https://medium.com/@rmfarber/libxsmm-brings-deep-learning-lessons-learned-to-many-hpc-applications-9143c6c93125</a>: LIBXSMM Brings Deep-learning "Lessons Learned" to Many HPC Applications. An article written by Rob Farber, 2018.</p> <p dir="auto"><b>[6] </b><a href="https://www.rdworldonline.com/largest-supercomputer-simulation-of-sumatra-andaman-earthquake/" rel="nofollow">https://www.rdworldonline.com/largest-supercomputer-simulation-of-sumatra-andaman-earthquake/</a>: Largest Supercomputer Simulation of Sumatra-Andaman Earthquake. An article written by Linda Barney, 2018.</p> </article></div></div></div></div></div> <!-- --> <!-- --> <script type="application/json" id="__PRIMER_DATA_:R0:__">{"resolvedServerColorMode":"day"}</script></div> </react-partial> <input type="hidden" data-csrf="true" value="I+f8fyA6ENoKjxNdy4B3nTP8ItTlUfZPLKkccaZqksMMVdGOYotGzJ9KtdmJ/dRkhGLBPVBxS1LovpmfMl5tSg==" /> </div> <div data-view-component="true" class="Layout-sidebar"> <div class="BorderGrid about-margin" data-pjax> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <div class="hide-sm hide-md"> <h2 class="mb-3 h4">About</h2> <p class="f4 my-3"> Library for specialized dense and sparse matrix operations, and deep learning primitives. </p> <div class="my-3 d-flex flex-items-center"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-link flex-shrink-0 mr-2"> <path d="m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z"></path> </svg> <span class="flex-auto min-width-0 css-truncate css-truncate-target width-fit"> <a title="https://libxsmm.readthedocs.io/" role="link" target="_blank" rel="noopener noreferrer nofollow" class="text-bold" href="https://libxsmm.readthedocs.io/">libxsmm.readthedocs.io/</a> </span> </div> <h3 class="sr-only">Topics</h3> <div class="my-3"> <div class="f6"> <a href="/topics/machine-learning" title="Topic: machine-learning" data-view-component="true" class="topic-tag topic-tag-link"> machine-learning </a> <a href="/topics/fortran" title="Topic: fortran" data-view-component="true" class="topic-tag topic-tag-link"> fortran </a> <a href="/topics/vector" title="Topic: vector" data-view-component="true" class="topic-tag topic-tag-link"> vector </a> <a href="/topics/matrix" title="Topic: matrix" data-view-component="true" class="topic-tag topic-tag-link"> matrix </a> <a href="/topics/intel" title="Topic: intel" data-view-component="true" class="topic-tag topic-tag-link"> intel </a> <a href="/topics/avx" title="Topic: avx" data-view-component="true" class="topic-tag topic-tag-link"> avx </a> <a href="/topics/sse" title="Topic: sse" data-view-component="true" class="topic-tag topic-tag-link"> sse </a> <a href="/topics/jit" title="Topic: jit" data-view-component="true" class="topic-tag topic-tag-link"> jit </a> <a href="/topics/simd" title="Topic: simd" data-view-component="true" class="topic-tag topic-tag-link"> simd </a> <a href="/topics/matrix-multiplication" title="Topic: matrix-multiplication" data-view-component="true" class="topic-tag topic-tag-link"> matrix-multiplication </a> <a href="/topics/sparse" title="Topic: sparse" data-view-component="true" class="topic-tag topic-tag-link"> sparse </a> <a href="/topics/blas" title="Topic: blas" data-view-component="true" class="topic-tag topic-tag-link"> blas </a> <a href="/topics/convolution" title="Topic: convolution" data-view-component="true" class="topic-tag topic-tag-link"> convolution </a> <a href="/topics/avx2" title="Topic: avx2" data-view-component="true" class="topic-tag topic-tag-link"> avx2 </a> <a href="/topics/amx" title="Topic: amx" data-view-component="true" class="topic-tag topic-tag-link"> amx </a> <a href="/topics/tensor" title="Topic: tensor" data-view-component="true" class="topic-tag topic-tag-link"> tensor </a> <a href="/topics/avx512" title="Topic: avx512" data-view-component="true" class="topic-tag topic-tag-link"> avx512 </a> <a href="/topics/transpose" title="Topic: transpose" data-view-component="true" class="topic-tag topic-tag-link"> transpose </a> <a href="/topics/bfloat16" title="Topic: bfloat16" data-view-component="true" class="topic-tag topic-tag-link"> bfloat16 </a> </div> </div> <h3 class="sr-only">Resources</h3> <div class="mt-2"> <a class="Link--muted" data-analytics-event="{"category":"Repository Overview","action":"click","label":"location:sidebar;file:readme"}" href="#readme-ov-file"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-book mr-2"> <path d="M0 1.75A.75.75 0 0 1 .75 1h4.253c1.227 0 2.317.59 3 1.501A3.743 3.743 0 0 1 11.006 1h4.245a.75.75 0 0 1 .75.75v10.5a.75.75 0 0 1-.75.75h-4.507a2.25 2.25 0 0 0-1.591.659l-.622.621a.75.75 0 0 1-1.06 0l-.622-.621A2.25 2.25 0 0 0 5.258 13H.75a.75.75 0 0 1-.75-.75Zm7.251 10.324.004-5.073-.002-2.253A2.25 2.25 0 0 0 5.003 2.5H1.5v9h3.757a3.75 3.75 0 0 1 1.994.574ZM8.755 4.75l-.004 7.322a3.752 3.752 0 0 1 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4.442c.313-.65.491-1.293.491-1.916v-.001c0-.614-.088-1.045-.23-1.385-.143-.339-.357-.633-.673-.949a3.111 3.111 0 0 0-2.218-.915c-1.092.003-2.165.627-3.226 1.602-.823.755-1.554 1.637-2.228 2.45l-.127.154.562.566a.755.755 0 0 0 1.066.02l.794-.79c1.258-1.258 3.312-1.31 4.594-.032.396.394.792.791 1.173 1.173Z"></path> </svg> Code of conduct </a> </div> <h3 class="sr-only">Security policy</h3> <div class="mt-2"> <a href="#security-ov-file" class="Link--muted" data-analytics-event="{"category":"Repository Overview","action":"click","label":"location:sidebar;file:security policy"}" > <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-law mr-2"> <path d="M8.75.75V2h.985c.304 0 .603.08.867.231l1.29.736c.038.022.08.033.124.033h2.234a.75.75 0 0 1 0 1.5h-.427l2.111 4.692a.75.75 0 0 1-.154.838l-.53-.53.529.531-.001.002-.002.002-.006.006-.006.005-.01.01-.045.04c-.21.176-.441.327-.686.45C14.556 10.78 13.88 11 13 11a4.498 4.498 0 0 1-2.023-.454 3.544 3.544 0 0 1-.686-.45l-.045-.04-.016-.015-.006-.006-.004-.004v-.001a.75.75 0 0 1-.154-.838L12.178 4.5h-.162c-.305 0-.604-.079-.868-.231l-1.29-.736a.245.245 0 0 0-.124-.033H8.75V13h2.5a.75.75 0 0 1 0 1.5h-6.5a.75.75 0 0 1 0-1.5h2.5V3.5h-.984a.245.245 0 0 0-.124.033l-1.289.737c-.265.15-.564.23-.869.23h-.162l2.112 4.692a.75.75 0 0 1-.154.838l-.53-.53.529.531-.001.002-.002.002-.006.006-.016.015-.045.04c-.21.176-.441.327-.686.45C4.556 10.78 3.88 11 3 11a4.498 4.498 0 0 1-2.023-.454 3.544 3.544 0 0 1-.686-.45l-.045-.04-.016-.015-.006-.006-.004-.004v-.001a.75.75 0 0 1-.154-.838L2.178 4.5H1.75a.75.75 0 0 1 0-1.5h2.234a.249.249 0 0 0 .125-.033l1.288-.737c.265-.15.564-.23.869-.23h.984V.75a.75.75 0 0 1 1.5 0Zm2.945 8.477c.285.135.718.273 1.305.273s1.02-.138 1.305-.273L13 6.327Zm-10 0c.285.135.718.273 1.305.273s1.02-.138 1.305-.273L3 6.327Z"></path> </svg> Security policy </a> </div> <include-fragment src="/libxsmm/libxsmm/hovercards/citation/sidebar_partial?tree_name=main"> </include-fragment> <div class="mt-2"> <a href="/libxsmm/libxsmm/activity" data-view-component="true" class="Link Link--muted"><svg text="gray" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-pulse mr-2"> <path d="M6 2c.306 0 .582.187.696.471L10 10.731l1.304-3.26A.751.751 0 0 1 12 7h3.25a.75.75 0 0 1 0 1.5h-2.742l-1.812 4.528a.751.751 0 0 1-1.392 0L6 4.77 4.696 8.03A.75.75 0 0 1 4 8.5H.75a.75.75 0 0 1 0-1.5h2.742l1.812-4.529A.751.751 0 0 1 6 2Z"></path> </svg> <span class="color-fg-muted">Activity</span></a> </div> <div class="mt-2"> <a href="/libxsmm/libxsmm/custom-properties" data-view-component="true" class="Link Link--muted"><svg text="gray" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-note mr-2"> <path d="M0 3.75C0 2.784.784 2 1.75 2h12.5c.966 0 1.75.784 1.75 1.75v8.5A1.75 1.75 0 0 1 14.25 14H1.75A1.75 1.75 0 0 1 0 12.25Zm1.75-.25a.25.25 0 0 0-.25.25v8.5c0 .138.112.25.25.25h12.5a.25.25 0 0 0 .25-.25v-8.5a.25.25 0 0 0-.25-.25ZM3.5 6.25a.75.75 0 0 1 .75-.75h7a.75.75 0 0 1 0 1.5h-7a.75.75 0 0 1-.75-.75Zm.75 2.25h4a.75.75 0 0 1 0 1.5h-4a.75.75 0 0 1 0-1.5Z"></path> </svg> <span class="color-fg-muted">Custom properties</span></a> </div> <h3 class="sr-only">Stars</h3> <div class="mt-2"> <a href="/libxsmm/libxsmm/stargazers" data-view-component="true" class="Link Link--muted"><svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-star mr-2"> <path d="M8 .25a.75.75 0 0 1 .673.418l1.882 3.815 4.21.612a.75.75 0 0 1 .416 1.279l-3.046 2.97.719 4.192a.751.751 0 0 1-1.088.791L8 12.347l-3.766 1.98a.75.75 0 0 1-1.088-.79l.72-4.194L.818 6.374a.75.75 0 0 1 .416-1.28l4.21-.611L7.327.668A.75.75 0 0 1 8 .25Zm0 2.445L6.615 5.5a.75.75 0 0 1-.564.41l-3.097.45 2.24 2.184a.75.75 0 0 1 .216.664l-.528 3.084 2.769-1.456a.75.75 0 0 1 .698 0l2.77 1.456-.53-3.084a.75.75 0 0 1 .216-.664l2.24-2.183-3.096-.45a.75.75 0 0 1-.564-.41L8 2.694Z"></path> </svg> <strong>867</strong> stars</a> </div> <h3 class="sr-only">Watchers</h3> <div class="mt-2"> <a href="/libxsmm/libxsmm/watchers" data-view-component="true" class="Link Link--muted"><svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-eye mr-2"> <path d="M8 2c1.981 0 3.671.992 4.933 2.078 1.27 1.091 2.187 2.345 2.637 3.023a1.62 1.62 0 0 1 0 1.798c-.45.678-1.367 1.932-2.637 3.023C11.67 13.008 9.981 14 8 14c-1.981 0-3.671-.992-4.933-2.078C1.797 10.83.88 9.576.43 8.898a1.62 1.62 0 0 1 0-1.798c.45-.677 1.367-1.931 2.637-3.022C4.33 2.992 6.019 2 8 2ZM1.679 7.932a.12.12 0 0 0 0 .136c.411.622 1.241 1.75 2.366 2.717C5.176 11.758 6.527 12.5 8 12.5c1.473 0 2.825-.742 3.955-1.715 1.124-.967 1.954-2.096 2.366-2.717a.12.12 0 0 0 0-.136c-.412-.621-1.242-1.75-2.366-2.717C10.824 4.242 9.473 3.5 8 3.5c-1.473 0-2.825.742-3.955 1.715-1.124.967-1.954 2.096-2.366 2.717ZM8 10a2 2 0 1 1-.001-3.999A2 2 0 0 1 8 10Z"></path> </svg> <strong>49</strong> watching</a> </div> <h3 class="sr-only">Forks</h3> <div class="mt-2"> <a href="/libxsmm/libxsmm/forks" data-view-component="true" class="Link Link--muted"><svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-repo-forked mr-2"> <path d="M5 5.372v.878c0 .414.336.75.75.75h4.5a.75.75 0 0 0 .75-.75v-.878a2.25 2.25 0 1 1 1.5 0v.878a2.25 2.25 0 0 1-2.25 2.25h-1.5v2.128a2.251 2.251 0 1 1-1.5 0V8.5h-1.5A2.25 2.25 0 0 1 3.5 6.25v-.878a2.25 2.25 0 1 1 1.5 0ZM5 3.25a.75.75 0 1 0-1.5 0 .75.75 0 0 0 1.5 0Zm6.75.75a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5Zm-3 8.75a.75.75 0 1 0-1.5 0 .75.75 0 0 0 1.5 0Z"></path> </svg> <strong>191</strong> forks</a> </div> <div class="mt-2"> <a class="Link--muted" href="/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Flibxsmm%2Flibxsmm&report=libxsmm+%28user%29"> Report repository </a> </div> </div> </div> </div> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <h2 class="h4 mb-3" data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame"> <a href="/libxsmm/libxsmm/releases" data-view-component="true" class="Link--primary no-underline Link">Releases <span title="50" data-view-component="true" class="Counter">50</span></a></h2> <a class="Link--primary d-flex no-underline" data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame" href="/libxsmm/libxsmm/releases/tag/1.17"> <svg aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-tag flex-shrink-0 mt-1 color-fg-success"> <path d="M1 7.775V2.75C1 1.784 1.784 1 2.75 1h5.025c.464 0 .91.184 1.238.513l6.25 6.25a1.75 1.75 0 0 1 0 2.474l-5.026 5.026a1.75 1.75 0 0 1-2.474 0l-6.25-6.25A1.752 1.752 0 0 1 1 7.775Zm1.5 0c0 .066.026.13.073.177l6.25 6.25a.25.25 0 0 0 .354 0l5.025-5.025a.25.25 0 0 0 0-.354l-6.25-6.25a.25.25 0 0 0-.177-.073H2.75a.25.25 0 0 0-.25.25ZM6 5a1 1 0 1 1 0 2 1 1 0 0 1 0-2Z"></path> </svg> <div class="ml-2 min-width-0"> <div class="d-flex"> <span class="css-truncate css-truncate-target text-bold mr-2" style="max-width: none;">Version 1.17</span> <span title="Label: Latest" data-view-component="true" class="Label Label--success flex-shrink-0"> Latest </span> </div> <div class="text-small color-fg-muted"><relative-time datetime="2021-12-03T09:00:21Z" class="no-wrap">Dec 3, 2021</relative-time></div> </div> </a> <div data-view-component="true" class="mt-3"> <a text="small" data-pjax="#repo-content-pjax-container" data-turbo-frame="repo-content-turbo-frame" href="/libxsmm/libxsmm/releases" data-view-component="true" class="Link">+ 49 releases</a></div> </div> </div> <div class="BorderGrid-row" hidden> <div class="BorderGrid-cell"> <include-fragment src="/libxsmm/libxsmm/used_by_list" accept="text/fragment+html"> </include-fragment> </div> </div> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <h2 class="h4 mb-3"> <a href="/libxsmm/libxsmm/graphs/contributors" data-view-component="true" class="Link--primary no-underline Link d-flex flex-items-center">Contributors <span title="54" data-view-component="true" class="Counter ml-1">54</span></a></h2> <ul class="list-style-none d-flex flex-wrap mb-n2"> <li class="mb-2 mr-2" > <a href="https://github.com/hfp" class="" data-hovercard-type="user" data-hovercard-url="/users/hfp/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/6748085?s=64&v=4" alt="@hfp" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/alheinecke" class="" data-hovercard-type="user" data-hovercard-url="/users/alheinecke/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/6407923?s=64&v=4" alt="@alheinecke" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/egeor" class="" data-hovercard-type="user" data-hovercard-url="/users/egeor/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/1154358?s=64&v=4" alt="@egeor" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/kunalbanerjee" class="" data-hovercard-type="user" data-hovercard-url="/users/kunalbanerjee/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/3120606?s=64&v=4" alt="@kunalbanerjee" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/narendrachaudhary51" class="" data-hovercard-type="user" data-hovercard-url="/users/narendrachaudhary51/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/26152063?s=64&v=4" alt="@narendrachaudhary51" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/maxhutch" class="" data-hovercard-type="user" data-hovercard-url="/users/maxhutch/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/1538980?s=64&v=4" alt="@maxhutch" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/deeptiag1" class="" data-hovercard-type="user" data-hovercard-url="/users/deeptiag1/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/44649298?s=64&v=4" alt="@deeptiag1" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/ska278" class="" data-hovercard-type="user" data-hovercard-url="/users/ska278/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/8258117?s=64&v=4" alt="@ska278" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/FreddieWitherden" class="" data-hovercard-type="user" data-hovercard-url="/users/FreddieWitherden/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/528611?s=64&v=4" alt="@FreddieWitherden" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/adelmanm" class="" data-hovercard-type="user" data-hovercard-url="/users/adelmanm/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/18640225?s=64&v=4" alt="@adelmanm" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/gregmhenry" class="" data-hovercard-type="user" data-hovercard-url="/users/gregmhenry/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/7854872?s=64&v=4" alt="@gregmhenry" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/ibhati" class="" data-hovercard-type="user" data-hovercard-url="/users/ibhati/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/74619854?s=64&v=4" alt="@ibhati" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/jspark1105" class="" data-hovercard-type="user" data-hovercard-url="/users/jspark1105/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/5545022?s=64&v=4" alt="@jspark1105" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> <li class="mb-2 mr-2" > <a href="https://github.com/breuera" class="" data-hovercard-type="user" data-hovercard-url="/users/breuera/hovercard" data-octo-click="hovercard-link-click" data-octo-dimensions="link_type:self" > <img src="https://avatars.githubusercontent.com/u/1843685?s=64&v=4" alt="@breuera" size="32" height="32" width="32" data-view-component="true" class="avatar circle" /> </a> </li> </ul> <div data-view-component="true" class="mt-3"> <a text="small" href="/libxsmm/libxsmm/graphs/contributors" data-view-component="true" class="Link--inTextBlock Link">+ 40 contributors</a></div> </div> </div> <div class="BorderGrid-row"> <div class="BorderGrid-cell"> <h2 class="h4 mb-3">Languages</h2> <div class="mb-2"> <span data-view-component="true" class="Progress"> <span style="background-color:#555555 !important;;width: 93.7%;" itemprop="keywords" data-view-component="true" class="Progress-item color-bg-success-emphasis"></span> <span style="background-color:#427819 !important;;width: 1.7%;" itemprop="keywords" data-view-component="true" class="Progress-item color-bg-success-emphasis"></span> <span style="background-color:#f34b7d !important;;width: 1.4%;" itemprop="keywords" data-view-component="true" class="Progress-item color-bg-success-emphasis"></span> <span style="background-color:#89e051 !important;;width: 1.2%;" itemprop="keywords" data-view-component="true" class="Progress-item color-bg-success-emphasis"></span> <span style="background-color:#3572A5 !important;;width: 1.0%;" itemprop="keywords" data-view-component="true" class="Progress-item color-bg-success-emphasis"></span> <span style="background-color:#4d41b1 !important;;width: 1.0%;" itemprop="keywords" data-view-component="true" class="Progress-item color-bg-success-emphasis"></span> </span></div> <ul class="list-style-none"> <li class="d-inline"> <a class="d-inline-flex flex-items-center flex-nowrap Link--secondary no-underline text-small mr-3" href="/libxsmm/libxsmm/search?l=c" data-ga-click="Repository, language stats search click, location:repo overview"> <svg style="color:#555555;" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-dot-fill mr-2"> <path d="M8 4a4 4 0 1 1 0 8 4 4 0 0 1 0-8Z"></path> </svg> <span class="color-fg-default text-bold mr-1">C</span> <span>93.7%</span> </a> </li> <li class="d-inline"> <a class="d-inline-flex flex-items-center flex-nowrap Link--secondary no-underline text-small mr-3" href="/libxsmm/libxsmm/search?l=makefile" data-ga-click="Repository, language stats search click, location:repo overview"> <svg style="color:#427819;" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-dot-fill mr-2"> <path d="M8 4a4 4 0 1 1 0 8 4 4 0 0 1 0-8Z"></path> </svg> <span class="color-fg-default text-bold mr-1">Makefile</span> <span>1.7%</span> </a> </li> <li class="d-inline"> <a class="d-inline-flex flex-items-center flex-nowrap Link--secondary no-underline text-small mr-3" href="/libxsmm/libxsmm/search?l=c%2B%2B" data-ga-click="Repository, language stats search click, location:repo overview"> <svg style="color:#f34b7d;" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-dot-fill mr-2"> <path d="M8 4a4 4 0 1 1 0 8 4 4 0 0 1 0-8Z"></path> </svg> <span class="color-fg-default text-bold mr-1">C++</span> <span>1.4%</span> </a> </li> <li class="d-inline"> <a class="d-inline-flex flex-items-center flex-nowrap Link--secondary no-underline text-small mr-3" href="/libxsmm/libxsmm/search?l=shell" data-ga-click="Repository, language stats search click, location:repo overview"> <svg style="color:#89e051;" aria-hidden="true" height="16" viewBox="0 0 16 16" version="1.1" width="16" data-view-component="true" class="octicon octicon-dot-fill mr-2"> <path d="M8 4a4 4 0 1 1 0 8 4 4 0 0 1 0-8Z"></path> </svg> <span class="color-fg-default text-bold mr-1">Shell</span> <span>1.2%</span> </a> </li> <li 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