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Fast-Accurate Full-Chip Dynamic Thermal Simulation With Fine Resolution Enabled by a Learning Method
The need for full-chip dynamic thermal simulation for effective runtime thermal management of multicore processors has been growing in recent years due to the rising demand for high-performance computing. In addition to simulation efficiency and accuracy, a high resolution is desirable in order to a...
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Published in: | IEEE transactions on computer-aided design of integrated circuits and systems 2023-08, Vol.42 (8), p.2675-2688 |
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description | The need for full-chip dynamic thermal simulation for effective runtime thermal management of multicore processors has been growing in recent years due to the rising demand for high-performance computing. In addition to simulation efficiency and accuracy, a high resolution is desirable in order to accurately predict crucial hot spots in the chip. This work investigates a simulation technique derived from proper orthogonal decomposition (POD) for full-chip dynamic thermal simulation of a multicore processor. The POD projects a heat transfer problem onto a mathematical space constituted by a finite set of basis functions (or POD modes) that are generated (or trained ) by thermal solution data collected from direct numerical simulation (DNS). Accuracy and efficiency of the POD simulation technique influenced by the quality of thermal data are examined thoroughly, especially in the areas with high thermal gradients. The results show that if the POD modes are trained by good-quality data, the POD simulation offers an accurate prediction of the dynamic thermal distribution in the multicore processor with an extremely small degree of freedom (DoF). A reduction in computational time over four orders of magnitude, compared to the DNS, can be achieved for full-chip dynamic thermal simulation with a resolution as fine as the DNS. The study has also demonstrated that the POD approach can be used to rigorously verify the accuracy of solutions offered by DNS tools. A practical approach is proposed to further enhance the accuracy and efficiency of the proposed full-chip thermal simulation technique. |
doi_str_mv | 10.1109/TCAD.2022.3229598 |
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In addition to simulation efficiency and accuracy, a high resolution is desirable in order to accurately predict crucial hot spots in the chip. This work investigates a simulation technique derived from proper orthogonal decomposition (POD) for full-chip dynamic thermal simulation of a multicore processor. The POD projects a heat transfer problem onto a mathematical space constituted by a finite set of basis functions (or POD modes) that are generated (or trained ) by thermal solution data collected from direct numerical simulation (DNS). Accuracy and efficiency of the POD simulation technique influenced by the quality of thermal data are examined thoroughly, especially in the areas with high thermal gradients. The results show that if the POD modes are trained by good-quality data, the POD simulation offers an accurate prediction of the dynamic thermal distribution in the multicore processor with an extremely small degree of freedom (DoF). A reduction in computational time over four orders of magnitude, compared to the DNS, can be achieved for full-chip dynamic thermal simulation with a resolution as fine as the DNS. The study has also demonstrated that the POD approach can be used to rigorously verify the accuracy of solutions offered by DNS tools. A practical approach is proposed to further enhance the accuracy and efficiency of the proposed full-chip thermal simulation technique.</description><identifier>ISSN: 0278-0070</identifier><identifier>EISSN: 1937-4151</identifier><identifier>DOI: 10.1109/TCAD.2022.3229598</identifier><identifier>CODEN: ITCSDI</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Accuracy ; Basis functions ; Computational modeling ; Computing time ; Data driven ; Data models ; Degrees of freedom ; Direct numerical simulation ; Efficiency ; full-chip thermal simulation ; Heat treating ; Integrated circuit modeling ; Integrated circuits ; Microprocessors ; model order reduction ; multicore processors ; Proper Orthogonal Decomposition ; proper orthogonal decomposition (POD) ; Simulation ; Solid modeling ; Space heating ; Temperature gradients ; Thermal management ; Thermal simulation</subject><ispartof>IEEE transactions on computer-aided design of integrated circuits and systems, 2023-08, Vol.42 (8), p.2675-2688</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-79a7239f2625e11eb48a6a089c1b9ef02c00223f1a2ccf1c79aa34fbe273342d3</citedby><cites>FETCH-LOGICAL-c293t-79a7239f2625e11eb48a6a089c1b9ef02c00223f1a2ccf1c79aa34fbe273342d3</cites><orcidid>0000-0002-0049-2071 ; 0000-0001-8092-5457 ; 0000-0001-9686-1726</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9987551$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,54795</link.rule.ids></links><search><creatorcontrib>Jiang, Lin</creatorcontrib><creatorcontrib>Liu, Yu</creatorcontrib><creatorcontrib>Cheng, Ming-C.</creatorcontrib><title>Fast-Accurate Full-Chip Dynamic Thermal Simulation With Fine Resolution Enabled by a Learning Method</title><title>IEEE transactions on computer-aided design of integrated circuits and systems</title><addtitle>TCAD</addtitle><description>The need for full-chip dynamic thermal simulation for effective runtime thermal management of multicore processors has been growing in recent years due to the rising demand for high-performance computing. In addition to simulation efficiency and accuracy, a high resolution is desirable in order to accurately predict crucial hot spots in the chip. This work investigates a simulation technique derived from proper orthogonal decomposition (POD) for full-chip dynamic thermal simulation of a multicore processor. The POD projects a heat transfer problem onto a mathematical space constituted by a finite set of basis functions (or POD modes) that are generated (or trained ) by thermal solution data collected from direct numerical simulation (DNS). Accuracy and efficiency of the POD simulation technique influenced by the quality of thermal data are examined thoroughly, especially in the areas with high thermal gradients. The results show that if the POD modes are trained by good-quality data, the POD simulation offers an accurate prediction of the dynamic thermal distribution in the multicore processor with an extremely small degree of freedom (DoF). A reduction in computational time over four orders of magnitude, compared to the DNS, can be achieved for full-chip dynamic thermal simulation with a resolution as fine as the DNS. The study has also demonstrated that the POD approach can be used to rigorously verify the accuracy of solutions offered by DNS tools. A practical approach is proposed to further enhance the accuracy and efficiency of the proposed full-chip thermal simulation technique.</description><subject>Accuracy</subject><subject>Basis functions</subject><subject>Computational modeling</subject><subject>Computing time</subject><subject>Data driven</subject><subject>Data models</subject><subject>Degrees of freedom</subject><subject>Direct numerical simulation</subject><subject>Efficiency</subject><subject>full-chip thermal simulation</subject><subject>Heat treating</subject><subject>Integrated circuit modeling</subject><subject>Integrated circuits</subject><subject>Microprocessors</subject><subject>model order reduction</subject><subject>multicore processors</subject><subject>Proper Orthogonal Decomposition</subject><subject>proper orthogonal decomposition (POD)</subject><subject>Simulation</subject><subject>Solid modeling</subject><subject>Space heating</subject><subject>Temperature gradients</subject><subject>Thermal management</subject><subject>Thermal simulation</subject><issn>0278-0070</issn><issn>1937-4151</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNo9kE1Lw0AQhhdRsFZ_gHhZ8Jy6O5s02WNJGxUqglY8LpvNxGzJR91NDv33TW3xNDA87zvMQ8g9ZzPOmXzapIvlDBjATADISCYXZMKliIOQR_ySTBjEScBYzK7JjfdbxngYgZyQItO-DxbGDE73SLOhroO0sju63Le6sYZuKnSNrumnbYZa97Zr6bftK5rZFukH-q4e_parVuc1FjTfU03XqF1r2x_6hn3VFbfkqtS1x7vznJKvbLVJX4L1-_NrulgHBqTog1jqGIQsYQ4Rco55mOi5Zok0PJdYMjBsfFCUXIMxJTcjr0VY5gixECEUYkoeT7071_0O6Hu17QbXjicVJEJGAMDmI8VPlHGd9w5LtXO20W6vOFNHmeooUx1lqrPMMfNwylhE_OelTOIo4uIA3W1vmQ</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Jiang, Lin</creator><creator>Liu, Yu</creator><creator>Cheng, Ming-C.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-0049-2071</orcidid><orcidid>https://orcid.org/0000-0001-8092-5457</orcidid><orcidid>https://orcid.org/0000-0001-9686-1726</orcidid></search><sort><creationdate>20230801</creationdate><title>Fast-Accurate Full-Chip Dynamic Thermal Simulation With Fine Resolution Enabled by a Learning Method</title><author>Jiang, Lin ; Liu, Yu ; Cheng, Ming-C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-79a7239f2625e11eb48a6a089c1b9ef02c00223f1a2ccf1c79aa34fbe273342d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Accuracy</topic><topic>Basis functions</topic><topic>Computational modeling</topic><topic>Computing time</topic><topic>Data driven</topic><topic>Data models</topic><topic>Degrees of freedom</topic><topic>Direct numerical simulation</topic><topic>Efficiency</topic><topic>full-chip thermal simulation</topic><topic>Heat treating</topic><topic>Integrated circuit modeling</topic><topic>Integrated circuits</topic><topic>Microprocessors</topic><topic>model order reduction</topic><topic>multicore processors</topic><topic>Proper Orthogonal Decomposition</topic><topic>proper orthogonal decomposition (POD)</topic><topic>Simulation</topic><topic>Solid modeling</topic><topic>Space heating</topic><topic>Temperature gradients</topic><topic>Thermal management</topic><topic>Thermal simulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jiang, Lin</creatorcontrib><creatorcontrib>Liu, Yu</creatorcontrib><creatorcontrib>Cheng, Ming-C.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on computer-aided design of integrated circuits and systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jiang, Lin</au><au>Liu, Yu</au><au>Cheng, Ming-C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fast-Accurate Full-Chip Dynamic Thermal Simulation With Fine Resolution Enabled by a Learning Method</atitle><jtitle>IEEE transactions on computer-aided design of integrated circuits and systems</jtitle><stitle>TCAD</stitle><date>2023-08-01</date><risdate>2023</risdate><volume>42</volume><issue>8</issue><spage>2675</spage><epage>2688</epage><pages>2675-2688</pages><issn>0278-0070</issn><eissn>1937-4151</eissn><coden>ITCSDI</coden><abstract>The need for full-chip dynamic thermal simulation for effective runtime thermal management of multicore processors has been growing in recent years due to the rising demand for high-performance computing. In addition to simulation efficiency and accuracy, a high resolution is desirable in order to accurately predict crucial hot spots in the chip. This work investigates a simulation technique derived from proper orthogonal decomposition (POD) for full-chip dynamic thermal simulation of a multicore processor. The POD projects a heat transfer problem onto a mathematical space constituted by a finite set of basis functions (or POD modes) that are generated (or trained ) by thermal solution data collected from direct numerical simulation (DNS). Accuracy and efficiency of the POD simulation technique influenced by the quality of thermal data are examined thoroughly, especially in the areas with high thermal gradients. The results show that if the POD modes are trained by good-quality data, the POD simulation offers an accurate prediction of the dynamic thermal distribution in the multicore processor with an extremely small degree of freedom (DoF). A reduction in computational time over four orders of magnitude, compared to the DNS, can be achieved for full-chip dynamic thermal simulation with a resolution as fine as the DNS. The study has also demonstrated that the POD approach can be used to rigorously verify the accuracy of solutions offered by DNS tools. A practical approach is proposed to further enhance the accuracy and efficiency of the proposed full-chip thermal simulation technique.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TCAD.2022.3229598</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-0049-2071</orcidid><orcidid>https://orcid.org/0000-0001-8092-5457</orcidid><orcidid>https://orcid.org/0000-0001-9686-1726</orcidid></addata></record> |
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subjects | Accuracy Basis functions Computational modeling Computing time Data driven Data models Degrees of freedom Direct numerical simulation Efficiency full-chip thermal simulation Heat treating Integrated circuit modeling Integrated circuits Microprocessors model order reduction multicore processors Proper Orthogonal Decomposition proper orthogonal decomposition (POD) Simulation Solid modeling Space heating Temperature gradients Thermal management Thermal simulation |
title | Fast-Accurate Full-Chip Dynamic Thermal Simulation With Fine Resolution Enabled by a Learning Method |
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