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btn-primary btn-lg" target="_blank" href="https://docs.nvidia.com/cuda/nvcomp/index.html">DOCUMENTATION <i class="fa fa-angle-right"></i></a> <a class="btn btn-primary btn-lg" target="_blank" href="https://github.com/NVIDIA/CUDALibrarySamples/tree/master/nvCOMP">EXAMPLES <i class="fa fa-angle-right"></i></a> <a class="btn btn-primary btn-lg" target="_blank" href="https://github.com/NVIDIA/CUDALibrarySamples/issues">SUPPORT <i class="fa fa-angle-right"></i></a> <a class="btn btn-primary btn-lg" target="_blank" href="mailto:Math-Libs-Feedback@nvidia.com?subject=nvCOMP%20Feedback&body=Thank%20you%20for%20using%20our%20software%20and%20taking%20time%20to%20provide%20your%20feedback.%0A%0AIf%20you%20have%20a%20question%20or%20issue%2C%20please%20post%20it%20on%20the%20CUDALibrarySamples%20GitHub%20Issues%20page%20at%3A%0A%0Ahttps%3A%2F%2Fgithub.com%2FNVIDIA%2FCUDALibrarySamples%2Fissues%0A%0A%0ATo%20submit%20a%20bug%20report%2C%20please%20follow%20the%20instructions%20at%3A%20%0A%0Ahttps%3A%2F%2Fforums.developer.nvidia.com%2Ft%2Fhow-to-report-a-bug%2F67911%0A%0A%0AProvide%20as%20much%20information%20and%20reproducer%20code%20as%20possible.%0A%0AFor%20feedback%20or%20feature%20requests%2C%20please%20reply%20to%20this%20email%20and%20provide%20the%20following%3A%0A%0A%20%201.%20Target%20Hardware%20(e.g.%20V100%2C%20A100%2C%20etc.)%0A%0A%20%202.%20Target%20OS%20(e.g.%20RHEL%208.1%2C%20Ubuntu%2020.04%2C%20Windows%2010%2C%20etc.)%0A%0A%20%203.%20Use%20cases%20(the%20more%20detail%20the%20better)%0A%0A%20%20%20%20%20a.%20Data%20type(s)%0A%0A%20%20%20%20%20b.%20Data%20size(s)%0A%0A%20%20%20%20%20c.%20Format(s)%0A%0A%20%204.%20Limiting%20factors%20by%20not%20having%20the%20desired%20functionality.">FEEDBACK <i class="fa fa-angle-right"></i></a> </p> <div class="section"> <div class="row"> <div class="col-md-12"> <p style="margin-top:1.5em;">The nvCOMP library provides fast lossless data compression and decompression using a GPU. It features generic compression interfaces to enable developers to use high-performance GPU compressors in their applications.</p> <p>Binaries are available under the standard <a target="_blank" href="https://developer.download.nvidia.com/compute/nvcomp/2.3/LICENSE.txt">NVIDIA Software License Agreement</a></p> </div> </div> </div> <div class="section"> <div class="row"> <div class="col-md-12"> <h3>nvCOMP Key Features</h3> <ul> <li> Compression Algorithms <ul> <li><a target="_blank" href="https://github.com/lz4/lz4">LZ4</a>: General-purpose no-entropy byte-level compressor well-suited for a wide range of datasets.</li> <li><a target="_blank" href="https://github.com/google/snappy/">Snappy</a>: Similar to LZ4, this byte-level compressor is a popular existing format used for tabular data.</li> <li><a href="/blog/accelerating-load-times-for-directx-games-and-apps-with-gdeflate-for-directstorage/">GDeflate</a>: A new compression format that closely matches the DEFLATE format and allows more efficient GPU decompression.</li> <li><a target="_blank" href="https://datatracker.ietf.org/doc/html/rfc1951">Deflate</a>: Huffman + LZ77, Provided for compatibility with existing Deflate-compressed datasets.</li> </li> <li><a target="_blank" href="https://github.com/facebook/zstd">zStandard</a>: Huffman + LZ77 + ANS, popular compression format developed by Meta.</li> </ul> </li> <li> NVIDIA-optimized Compression Formats (use nvCOMP to compress/decompress) <ul> <li> <a target="_blank" href="https://docs.nvidia.com/cuda/nvcomp/cascaded.html">Cascaded:</a> Novel high-throughput compressor ideal for analytical or structured/tabular data. </li> <li>Bitcomp: Proprietary compressor designed for efficient GPU compression in Scientific Computing applications.</li> <li>ANS: Proprietary entropy encoder based on asymmetric numeral systems (ANS)</li> </ul> </li> </ul> </div> </div> </div> <div class="section"> <div class="row"> <div class="col-md-12"> <h3>nvCOMP Performance</h3> <div class="col-md-12 img-responsive-wrapper padding-md-bottom"> <center> <a target="_blank" href="https://d29g4g2dyqv443.cloudfront.net/sites/default/files/3.0nvCOMPResults.PNG"> <img class="img-responsive" style=" width:100%;" src="https://d29g4g2dyqv443.cloudfront.net/sites/default/files/3.0nvCOMPResults.PNG"></a> <br> </center> <br> </div> <div> <!-- <p>The table below shows GPU compression throughput results in GB/s for a wide range of Ampere architecture GPU products, datasets and compression methods.</p> --> <br> <p>For additional information, please see our technical blogs and presentations:</p> <ul> <li><a target="_blank" href="https://developer.nvidia.com/blog/accelerating-lossless-gpu-compression-with-new-flexible-interfaces-in-nvidia-nvcomp/">Accelerating Lossless GPU Compression with New Flexible Interfaces in NVIDIA nvCOMP</a></li> <li><a target="_blank" href="https://developer.nvidia.com/blog/optimizing-data-transfer-using-lossless-compression-with-nvcomp/">Optimizing Data Transfer Using Lossless Compression with nvCOMP</a></li> <li><a target="_blank" href="https://gtc21.event.nvidia.com/media/Optimizing%20Lossless%20Compression%20Algorithms%20on%20the%20GPU%20%5BS32401%5D/1_ponxuymy">Optimizing Lossless Compression Algorithms on the GPU</a></li> </ul> <p>Also feel free to gather your own results by running the <a target="_blank" href="https://github.com/NVIDIA/CUDALibrarySamples/tree/master/nvCOMP/benchmarks">benchmarks</a>.</p> </div> </div> </div> </div> <br> <br> <div class="container"> <div class="row"> <div class="col-12" style="margin-top: 1em; 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'true' : 'false', ''], ['chartLegend', JSON.stringify(legendData), ''], ['xAxisLabel', xAxisLabel, ''], ['barPadding', barPadding, 5], ['chartBars', bars, ''], ['chartTicks', ticks, ''], ]; dataAttributes.forEach(dataAttribute => { if (dataAttribute[0] === 'chartBars' && dataAttribute[1]) { dataAttribute[1] = JSON.stringify(dataAttribute[1]); } if (dataAttribute[0] === 'chartTicks' && dataAttribute[1]) { dataAttribute[1] = JSON.stringify(dataAttribute[1]); } svgElement.dataset[dataAttribute[0]] = dataAttribute[1] ? dataAttribute[1] : dataAttribute[2]; }); // Caption if (footNote) { element.querySelector('.chart-footnote').innerHTML = footNote; } else { element.querySelector('.chart-footnote').remove(); } // Init chart const chartContainer = element.querySelector('.chart-container'); setTimeout(function () { if (jQuery(chartContainer).is(':visible')) { chartInit(chartContainer); } }, 300); }); }) } } window.customElements.define('horizontal-chart', HorizontalChartElement); </script> <script src="https://dirms4qsy6412.cloudfront.net/assets/tablefilter/tablefilter-e8295498b8f34d53fbb98264abcc88fb72c57915ee6a13b15361d5df0127ebbb.js"></script> <template id="nv-filtered-table-template"> <div class="nvidia-filtered-table-wrapper"></div> </template> <script> const buildTableIdentity = (function (str) { let counter = 0; return function (str) {counter += 1; return `${str}-${counter}`} })(); function slugify(str) { return String(str) .normalize('NFKD') // split accented characters into their base characters and diacritical marks .replace(/[\u0300-\u036f]/g, '') // remove all the accents, which happen to be all in the \u03xx UNICODE block. .trim() // trim leading or trailing whitespace .toLowerCase() // convert to lowercase .replace(/[^a-z0-9 -]/g, '') // remove non-alphanumeric characters .replace(/\s+/g, '-') // replace spaces with hyphens .replace(/-+/g, '-'); // remove consecutive hyphens } /** * Returns URL params. * * @returns {any|{[p: string]: string}} */ function getUrlParams() { try { return Object.fromEntries(new URLSearchParams(location.search)); } catch (e) { // Fallback for IE11. let search = location.search.substring(1) .replace(/&/g, '","') .replace(/=/g, '":"'); return JSON.parse('{"' + search + '"}', function (key, value) { return key === "" ? value : decodeURIComponent(value); }); } } /** * Query string extension for TableFilter. * * @see http://www.tablefilter.com/extension-run-time.html * * @param {Object} tf * TableFilter instance. * @constructor */ function QueryStringExtension(tf) { this.tf = tf; } QueryStringExtension.prototype.init = function () { let tf = this.tf; tf.emitter.on(['after-filtering'], this.afterFiltering.bind(this)); }; QueryStringExtension.prototype.afterFiltering = function (tf, terms) { const config = tf.cfg; // Get query string. let existingParams = getUrlParams(); // Remove values related to current table. $.each(terms, function (index, element) { let key = config.qs_filters[index]; delete existingParams[config.table_identity + "_" + key]; }); $.each(terms, function (index, element) { if (element.length) { existingParams[config.table_identity + "_" + config.qs_filters[index]] = element; } }); const paramsKeys = Object.keys(existingParams).sort(); let sortedParams = {}; $.each(paramsKeys, function (i, e) { sortedParams[e] = existingParams[e]; }); const params = $.param(sortedParams); const url = window.location.pathname + '?' + decodeURI(params); window.history.replaceState({}, '', url); }; function addQueryStringExtension(tf) { let queryStringExtension = new QueryStringExtension(tf); try { tf.registerExtension(queryStringExtension, 'queryStringExtension'); queryStringExtension.init(); } catch (e) { console.log('Failed to init URL params handler.'); } } /** * Filtered table web component. */ class NvFilteredTableWebComponent extends HTMLElement { constructor() { super(); const elementTemplate = document.getElementById('nv-filtered-table-template'); this._shadowRoot = this.attachShadow({'mode': 'open'}); this._shadowRoot.appendChild(elementTemplate.content.cloneNode(true)); } async loadSourceFile(url) { try { const response = await fetch(url); return response.json(); } catch (e) { console.warn(`Failed to load table data. URL: ${url}`); } return {}; } fetchComponentData = (url, el, hash) => this.loadSourceFile(url).then((data) => this.instantiateComponent(data, el, hash)); getColumnTypes(config) { return Array.from(config).map((col) => { const {columnType} = col; return columnType ? columnType : 'string'; }); } addFilterWidgets(config, headerData) { headerData.forEach((col, idx) => { const {filterWidget} = col; if (filterWidget) { config[`col_${idx}`] = filterWidget; } }); return config; } instantiateComponent(data, element, hash) { const {tableIndex: headerData, tableItems: rowsData, tableIdentity} = data; let filterConfig = { base_path: '/', sticky_headers: true, alternate_rows: true, mark_active_columns: { highlight_column: true, }, loader: true, highlight_keywords: true, no_results_message: true, toolbar: false, help_instructions: false, paging: { results_per_page: ['Records: ', [25, 50, 100]] }, auto_filter: true, responsive: true, grid_layout: { width: '100%', tbl_cont_css_class: 'nvidia-filtered-table' }, clear_filter_text: 'All', col_types: this.getColumnTypes(headerData), extensions: [ {name: ''} ], flt_css_class: 'filter-control', on_filters_loaded: (e) => { const {cfg} = e; if (!cfg) { return; } const {defaultValues} = cfg; if(!Array.isArray(defaultValues)) { return; } if (defaultValues.length === 0) { return; } defaultValues.forEach((defaultValue) => { const {index, value} = defaultValue; let headerCell = document.querySelector('.header-row th[data-idx="' + index + '"]'); if (!headerCell) { return; } const filterIndex = headerCell.dataset['fidx']; e.setFilterValue(filterIndex, value); }); e.filter(); }, qs_filters: headerData.map((item) => { return slugify(item?.columnName); }), }; filterConfig = this.addFilterWidgets(filterConfig, headerData); const id = tableIdentity ? tableIdentity : buildTableIdentity('t'); filterConfig.table_identity = id; const defaultValues = headerData .filter(item => item?.defaultValue !== undefined) .map(item => { return {index: item['column'], value: item['defaultValue']}; }); const filtersMap = headerData.map(item => { const {columnName, column} = item; return { index: column, key: `${id}_${slugify(columnName)}`} }); const sp = new URLSearchParams(location.search); filtersMap.forEach(filter => { if (!sp.has(filter.key)) { return; } defaultValues.push({index: filter.index, value: sp.get(filter.key)}); }); const detail = { hash, headerData, rowsData, defaultValues, filterConfig: { table_identity: id, config: filterConfig, predefined_selects: JSON.stringify([]), labels_width: [], }, }; const event = new CustomEvent('nv.filterTable.build', {detail}); document.dispatchEvent(event); } connectedCallback() { const url = this.getAttribute('source'); const hash = this.getAttribute('data-hash'); const element = this._shadowRoot; document.addEventListener('DOMContentLoaded', () => this.fetchComponentData(url, element, hash)); } } // Register web component. window.customElements.define('nv-filtered-table', NvFilteredTableWebComponent); /** * Builds table header. * * @param {Array} data * @param {HTMLElement} parentElement */ const buildHeader = (data, parentElement) => { data.forEach((item, idx) => { const {column, columnName} = item; const cell = document.createElement('th') cell.dataset['idx'] = column; cell.dataset['fidx'] = idx; cell.innerHTML = columnName; const {labelWidth, columnWidth} = item; if (labelWidth) { cell.dataset['label_width'] = labelWidth; } if (columnWidth && Number.isInteger(columnWidth) && columnWidth > 0) { cell.width = columnWidth + '%'; } else if (columnWidth && (columnWidth.endsWith('em') || columnWidth.endsWith('px') || columnWidth.endsWith('%'))) { cell.width = columnWidth; } parentElement.appendChild(cell); }); } /** * Builds table rows. * * @param {Object} headerData * @param {Array} data * @param {HTMLElement} parentElement */ const buildRows = (headerData, data, parentElement) => { data.forEach(partner => { const {name, logo, URL: partnerUrl, cameras} = partner; const logoCellContent = ` <a href="${partnerUrl}"> <img src="${logo}" alt="${name}" title="${name}" loading="lazy"> </a> <span class="element-invisible">${name}</span> `; cameras.forEach(camera => { const row = document.createElement('tr'); const logoCell = document.createElement('td'); logoCell.innerHTML = logoCellContent; row.appendChild(logoCell); for (const [key, value] of Object.entries(headerData)) { if (!camera[value.column]) { continue; } const cell = document.createElement('td'); let cameraValue = camera[value.column]; let cellHTML = ''; if (typeof cameraValue === 'object') { const {type, product_url, product_img, td_text} = cameraValue let img = ''; if(product_img !== "—") { img = `<img src="${product_img}" alt="${td_text}" title="${td_text}">`; } let html = ` <div class="product-link"> <a href="${product_url}" target="_blank"> ${img} <div class="product-title">${td_text}</div> </a> </div>` cellHTML = html.trim(); } else if (typeof cameraValue === 'string') { cellHTML = cameraValue } cell.innerHTML = cellHTML; row.appendChild(cell); } parentElement.appendChild(row); }) }); } const initTable = (table, filtersConfig, defaultValues) => { filtersConfig.config.defaultValues = defaultValues; const nvidiaFilteredTable = new TableFilter(table, filtersConfig.config); nvidiaFilteredTable.emitter.on(['before-loading-extensions'], addQueryStringExtension); nvidiaFilteredTable.init(); }; document.addEventListener('nv.filterTable.build', (event) => { const {detail} = event; const {headerData, rowsData, filterConfig, hash, defaultValues} = detail; const component = document.querySelector('nv-filtered-table[data-hash="' + hash + '"]'); const element = document.createElement('div'); element.classList.add('nvidia-filtered-table-wrapper'); element.innerHTML = `<div class="table-responsive"><table class="table table-hover table-striped sticky-enabled"><thead></thead><tbody></tbody></table></div>`; component.after(element); const table = element.querySelector('table'); const tableHeader = element.querySelector('table thead'); const tableHeaderRow = document.createElement('tr'); tableHeaderRow.classList.add('header-row'); tableHeader.appendChild(tableHeaderRow); buildHeader(headerData, tableHeaderRow); const tableBody = element.querySelector('table tbody'); buildRows(headerData, rowsData, tableBody); initTable(table, filterConfig, defaultValues); 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