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</div> </div> <div id="bodyContent" class="vector-body" aria-labelledby="firstHeading" data-mw-ve-target-container> <div class="vector-body-before-content"> <div class="mw-indicators"> </div> <div id="siteSub" class="noprint">From Wikipedia, the free encyclopedia</div> </div> <div id="contentSub"><div id="mw-content-subtitle"></div></div> <div id="mw-content-text" class="mw-body-content"><div class="mw-content-ltr mw-parser-output" lang="en" dir="ltr"><div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none">Measure of neuronal network performance</div> <p>In <a href="/wiki/Computational_neuroscience" title="Computational neuroscience">computational neuroscience</a>, <b>SUPS</b> (for <b>S</b>ynaptic <b>U</b>pdates <b>P</b>er <b>S</b>econd) or formerly CUPS (<b>C</b>onnections <b>U</b>pdates <b>P</b>er <b>S</b>econd) is a measure of a neuronal network performance, useful in fields of <a href="/wiki/Neuroscience" title="Neuroscience">neuroscience</a>, <a href="/wiki/Cognitive_science" title="Cognitive science">cognitive science</a>, <a href="/wiki/Artificial_intelligence" title="Artificial intelligence">artificial intelligence</a>, and <a href="/wiki/Computer_science" title="Computer science">computer science</a>. </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="Computing">Computing</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SUPS&action=edit&section=1" title="Edit section: Computing"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>For a processor or computer designed to simulate a neural network SUPS is measured as the product of simulated neurons <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle N}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>N</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle N}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/f5e3890c981ae85503089652feb48b191b57aae3" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:2.064ex; height:2.176ex;" alt="{\displaystyle N}"></span> and average connectivity <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle c}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>c</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle c}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/86a67b81c2de995bd608d5b2df50cd8cd7d92455" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.007ex; height:1.676ex;" alt="{\displaystyle c}"></span>(synapses) per neuron per second: </p><p><span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle SUPS=c\times N}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>S</mi> <mi>U</mi> <mi>P</mi> <mi>S</mi> <mo>=</mo> <mi>c</mi> <mo>×</mo> <mi>N</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle SUPS=c\times N}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/356b5b355d85d01980e6050a9aa7d80780d71dcb" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:15.536ex; height:2.176ex;" alt="{\displaystyle SUPS=c\times N}"></span> </p><p>Depending on the type of simulation it is usually equal to the total number of synapses simulated. </p><p>In an "asynchronous" dynamic simulation if a neuron spikes at <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \upsilon }"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>υ</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \upsilon }</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/d3d9773c30e2bda2ecb0af8fa63f9e0e537f0fc4" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.255ex; height:1.676ex;" alt="{\displaystyle \upsilon }"></span> Hz, the average rate of synaptic updates provoked by the activity of that neuron is <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \upsilon cN}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>υ</mi> <mi>c</mi> <mi>N</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \upsilon cN}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/a4b4dda4cad2a82df11bbd6f6dc601a186d97c4f" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:4.326ex; height:2.176ex;" alt="{\displaystyle \upsilon cN}"></span>. In a synchronous simulation with step <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \Delta t}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi mathvariant="normal">Δ</mi> <mi>t</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \Delta t}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/8c28867ecd34e2caed12cf38feadf6a81a7ee542" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:2.775ex; height:2.176ex;" alt="{\displaystyle \Delta t}"></span> the number of synaptic updates per second would be <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle {\frac {cN}{\Delta t}}}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mrow class="MJX-TeXAtom-ORD"> <mfrac> <mrow> <mi>c</mi> <mi>N</mi> </mrow> <mrow> <mi mathvariant="normal">Δ</mi> <mi>t</mi> </mrow> </mfrac> </mrow> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle {\frac {cN}{\Delta t}}}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/d7171ce9c88a066f68e6ff1901af973f126eb688" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -2.005ex; width:3.907ex; height:5.343ex;" alt="{\displaystyle {\frac {cN}{\Delta t}}}"></span>. As <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \Delta t}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi mathvariant="normal">Δ</mi> <mi>t</mi> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \Delta t}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/8c28867ecd34e2caed12cf38feadf6a81a7ee542" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:2.775ex; height:2.176ex;" alt="{\displaystyle \Delta t}"></span> has to be chosen much smaller than the average interval between two successive afferent spikes, which implies <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \Delta t<{\frac {1}{\upsilon N}}}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi mathvariant="normal">Δ</mi> <mi>t</mi> <mo><</mo> <mrow class="MJX-TeXAtom-ORD"> <mfrac> <mn>1</mn> <mrow> <mi>υ</mi> <mi>N</mi> </mrow> </mfrac> </mrow> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \Delta t<{\frac {1}{\upsilon N}}}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/c6c1275d2fba85d12231e6450f6e3ac0a5b4b748" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -1.838ex; width:10.029ex; height:5.176ex;" alt="{\displaystyle \Delta t<{\frac {1}{\upsilon N}}}"></span>, giving an average of synaptic updates equal to <span class="mwe-math-element"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \upsilon cN^{2}}"> <semantics> <mrow class="MJX-TeXAtom-ORD"> <mstyle displaystyle="true" scriptlevel="0"> <mi>υ</mi> <mi>c</mi> <msup> <mi>N</mi> <mrow class="MJX-TeXAtom-ORD"> <mn>2</mn> </mrow> </msup> </mstyle> </mrow> <annotation encoding="application/x-tex">{\displaystyle \upsilon cN^{2}}</annotation> </semantics> </math></span><img src="https://wikimedia.org/api/rest_v1/media/math/render/svg/ac1e4c4a5e2e6624d99aef124fe6f1a6dd15d67d" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:5.439ex; height:2.676ex;" alt="{\displaystyle \upsilon cN^{2}}"></span>. Therefore, spike-driven synaptic dynamics leads to a linear scaling of computational complexity <a href="/wiki/Big_O_notation" title="Big O notation">O</a>(N) per neuron, compared with the O(N<sup>2</sup>) in the "synchronous" case.<sup id="cite_ref-Mattia1998_1-0" class="reference"><a href="#cite_note-Mattia1998-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Records">Records</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SUPS&action=edit&section=2" title="Edit section: Records"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Developed in the 1980s Adaptive Solutions' CNAPS-1064 Digital Parallel Processor chip is a full <a href="/wiki/Neurochip" title="Neurochip">neural network (NNW)</a>. It was designed as a <a href="/wiki/Coprocessor" title="Coprocessor">coprocessor</a> to a host and has 64 sub-processors arranged in a <a href="/wiki/Network_topology" title="Network topology">1D array</a> and operating in a <a href="/wiki/SIMD" class="mw-redirect" title="SIMD">SIMD</a> mode. Each sub-processor can emulate one or more neurons and multiple chips can be grouped together. At 25 MHz it is capable of 1.28 <a href="/wiki/Multiply%E2%80%93accumulate_operation" title="Multiply–accumulate operation">GMAC</a>.<sup id="cite_ref-Weems_2-0" class="reference"><a href="#cite_note-Weems-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> </p><p>After the presentation of the RN-100 (12 MHz) single neuron chip at Seattle 1991 <a href="/wiki/Ricoh" title="Ricoh">Ricoh</a> developed the multi-neuron chip RN-200. It had 16 neurons and 16 synapses per neuron. The chip has on-chip learning ability using a proprietary backdrop algorithm. It came in a 257-pin <a href="/wiki/Pin_grid_array" title="Pin grid array">PGA</a> encapsulation and drew 3.0 W at a maximum. It was capable of 3 GCPS (1 GCPS at 32 MHz). <sup id="cite_ref-Almeida2003_3-0" class="reference"><a href="#cite_note-Almeida2003-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> </p><p>In 1991–97, <a href="/wiki/Siemens" title="Siemens">Siemens</a> developed the MA-16 chip, SYNAPSE-1 and SYNAPSE-3 Neurocomputer. The MA-16 was a fast matrix-matrix multiplier that can be combined to form <a href="/wiki/Systolic_array" title="Systolic array">systolic arrays</a>. It could process 4 patterns of 16 elements each (16-bit), with 16 neuron values (16-bit) at a rate of 800 MMAC or 400 MCPS at 50 MHz. The SYNAPSE3-PC <a href="/wiki/Conventional_PCI" class="mw-redirect" title="Conventional PCI">PCI card</a> contained 2 MA-16 with a peak performance of 2560 MOPS (1.28 GMAC); 7160 MOPS (3.58 GMAC) when using three boards.<sup id="cite_ref-Lindsey1998_4-0" class="reference"><a href="#cite_note-Lindsey1998-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> </p><p>In 2013, the <a href="/wiki/K_computer" title="K computer">K computer</a> was used to simulate a neural network of 1.73 billion neurons with a total of 10.4 trillion synapses (1% of the human brain). The simulation ran for 40 minutes to simulate 1 s of brain activity at a normal activity level (4.4 on average). The simulation required 1 Petabyte of storage.<sup id="cite_ref-CNET20130805_5-0" class="reference"><a href="#cite_note-CNET20130805-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SUPS&action=edit&section=3" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/FLOP" class="mw-redirect" title="FLOP">FLOP</a></li> <li><a href="/wiki/SPECint" title="SPECint">SPECint</a></li> <li><a href="/wiki/SPECfp" title="SPECfp">SPECfp</a></li> <li><a href="/wiki/Multiply%E2%80%93accumulate_operation" title="Multiply–accumulate operation">Multiply–accumulate operation</a></li> <li><a href="/wiki/Orders_of_magnitude_(computing)" class="mw-redirect" title="Orders of magnitude (computing)">Orders of magnitude (computing)</a></li> <li><a href="/wiki/SyNAPSE" title="SyNAPSE">SyNAPSE</a></li></ul> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=SUPS&action=edit&section=4" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1239543626">.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist .references{font-size:100%;margin-bottom:0;list-style-type:inherit}.mw-parser-output .reflist-columns-2{column-width:30em}.mw-parser-output .reflist-columns-3{column-width:25em}.mw-parser-output .reflist-columns{margin-top:0.3em}.mw-parser-output .reflist-columns ol{margin-top:0}.mw-parser-output .reflist-columns li{page-break-inside:avoid;break-inside:avoid-column}.mw-parser-output .reflist-upper-alpha{list-style-type:upper-alpha}.mw-parser-output .reflist-upper-roman{list-style-type:upper-roman}.mw-parser-output .reflist-lower-alpha{list-style-type:lower-alpha}.mw-parser-output .reflist-lower-greek{list-style-type:lower-greek}.mw-parser-output .reflist-lower-roman{list-style-type:lower-roman}</style><div class="reflist reflist-columns references-column-width" style="column-width: 30em;"> <ol class="references"> <li id="cite_note-Mattia1998-1"><span class="mw-cite-backlink"><b><a href="#cite_ref-Mattia1998_1-0">^</a></b></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}</style><cite id="CITEREFMaurizio_MattiaPaolo_Del_Giudice1998" class="citation book cs1">Maurizio Mattia; Paolo Del Giudice (1998). "Asynchronous simulation of large networks of spiking neurons and dynamical synapses". <a href="/wiki/Spiking_neuron" class="mw-redirect" title="Spiking neuron"><i>Icann 98</i></a>. Perspectives in Neural Computing. pp. 1045–1050. <a href="/wiki/CiteSeerX_(identifier)" class="mw-redirect" title="CiteSeerX (identifier)">CiteSeerX</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.272">10.1.1.56.272</a></span>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1007%2F978-1-4471-1599-1_164">10.1007/978-1-4471-1599-1_164</a>. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-3-540-76263-8" title="Special:BookSources/978-3-540-76263-8"><bdi>978-3-540-76263-8</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=bookitem&rft.atitle=Asynchronous+simulation+of+large+networks+of+spiking+neurons+and+dynamical+synapses&rft.btitle=Icann+98&rft.series=Perspectives+in+Neural+Computing&rft.pages=1045-1050&rft.date=1998&rft_id=https%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fsummary%3Fdoi%3D10.1.1.56.272%23id-name%3DCiteSeerX&rft_id=info%3Adoi%2F10.1007%2F978-1-4471-1599-1_164&rft.isbn=978-3-540-76263-8&rft.au=Maurizio+Mattia&rft.au=Paolo+Del+Giudice&rfr_id=info%3Asid%2Fen.wikipedia.org%3ASUPS" class="Z3988"></span></span> </li> <li id="cite_note-Weems-2"><span class="mw-cite-backlink"><b><a href="#cite_ref-Weems_2-0">^</a></b></span> <span class="reference-text"><a rel="nofollow" class="external text" href="ftp://ftp.cs.umass.edu/pub/osl/papers/uPSurvey-TR-95-42.ps.Z"><i>Real-Time Computing: Implications for General Microprocessors</i></a> Chip Weems, Steve Dropsho</span> </li> <li id="cite_note-Almeida2003-3"><span class="mw-cite-backlink"><b><a href="#cite_ref-Almeida2003_3-0">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFL._AlmeidaLuis_B._AlmeidaS._Boverie2003" class="citation book cs1">L. Almeida; Luis B. Almeida; S. Boverie (2003). <a rel="nofollow" class="external text" href="https://books.google.com/books?id=pDFdub32IdYC"><i>Intelligent Components and Instruments For Control Applications 2003 (SICICA 2003)</i></a>. Elsevier. <a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/9780080440101" title="Special:BookSources/9780080440101"><bdi>9780080440101</bdi></a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=book&rft.btitle=Intelligent+Components+and+Instruments+For+Control+Applications+2003+%28SICICA+2003%29&rft.pub=Elsevier&rft.date=2003&rft.isbn=9780080440101&rft.au=L.+Almeida&rft.au=Luis+B.+Almeida&rft.au=S.+Boverie&rft_id=https%3A%2F%2Fbooks.google.com%2Fbooks%3Fid%3DpDFdub32IdYC&rfr_id=info%3Asid%2Fen.wikipedia.org%3ASUPS" class="Z3988"></span></span> </li> <li id="cite_note-Lindsey1998-4"><span class="mw-cite-backlink"><b><a href="#cite_ref-Lindsey1998_4-0">^</a></b></span> <span class="reference-text"><a rel="nofollow" class="external text" href="http://neuralnets.web.cern.ch/NeuralNets/nnwinhephard.html"><i>Neural Network Hardware</i></a> Clark S. Lindsey, Bruce Denby, Thomas Lindblad, 1998</span> </li> <li id="cite_note-CNET20130805-5"><span class="mw-cite-backlink"><b><a href="#cite_ref-CNET20130805_5-0">^</a></b></span> <span class="reference-text"><a rel="nofollow" class="external text" href="https://www.cnet.com/news/fujitsu-supercomputer-simulates-1-second-of-brain-activity/"><i>Fujitsu supercomputer simulates 1 second of brain activity</i></a> Tim Hornyak, CNET, August 5, 2013</span> </li> </ol></div>    </div><noscript><img src="https://login.wikimedia.org/wiki/Special:CentralAutoLogin/start?type=1x1" alt="" width="1" height="1" style="border: none; position: absolute;"></noscript> <div class="printfooter" data-nosnippet="">Retrieved from "<a dir="ltr" href="https://en.wikipedia.org/w/index.php?title=SUPS&oldid=1219174059">https://en.wikipedia.org/w/index.php?title=SUPS&oldid=1219174059</a>"</div></div> <div id="catlinks" class="catlinks" data-mw="interface"><div id="mw-normal-catlinks" class="mw-normal-catlinks"><a href="/wiki/Help:Category" title="Help:Category">Categories</a>: <ul><li><a href="/wiki/Category:Benchmarks_(computing)" title="Category:Benchmarks (computing)">Benchmarks (computing)</a></li><li><a href="/wiki/Category:Units_of_frequency" title="Category:Units of frequency">Units of frequency</a></li><li><a href="/wiki/Category:Artificial_intelligence" title="Category:Artificial intelligence">Artificial intelligence</a></li><li><a href="/wiki/Category:Computational_neuroscience" title="Category:Computational neuroscience">Computational neuroscience</a></li><li><a href="/wiki/Category:Neurotechnology" title="Category:Neurotechnology">Neurotechnology</a></li></ul></div><div id="mw-hidden-catlinks" class="mw-hidden-catlinks mw-hidden-cats-hidden">Hidden categories: <ul><li><a href="/wiki/Category:Articles_with_short_description" title="Category:Articles with short description">Articles with short description</a></li><li><a href="/wiki/Category:Short_description_matches_Wikidata" title="Category:Short description matches Wikidata">Short description matches Wikidata</a></li></ul></div></div> </div> </main> </div> <div class="mw-footer-container"> <footer id="footer" class="mw-footer" > <ul id="footer-info"> <li id="footer-info-lastmod"> This page was last edited on 16 April 2024, at 05:23<span class="anonymous-show"> (UTC)</span>.</li> <li id="footer-info-copyright">Text is available under the <a href="/wiki/Wikipedia:Text_of_the_Creative_Commons_Attribution-ShareAlike_4.0_International_License" title="Wikipedia:Text of the Creative Commons Attribution-ShareAlike 4.0 International License">Creative Commons Attribution-ShareAlike 4.0 License</a>; additional terms may apply. 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