TY - GEN
T1 - A Spectral Approach to Scalable Vectorless Thermal Integrity Verification
AU - Zhao, Zhiqiang
AU - Feng, Zhuo
N1 - Publisher Copyright:
© 2020 EDAA.
PY - 2020/3
Y1 - 2020/3
N2 - Existing chip thermal analysis and verification methods require detailed distribution of power densities or modeling of underlying input workloads (vectors), which may not always be feasible at early-design stage. This paper introduces the first vectorless thermal integrity verification framework that allows computing worst-case temperature (gradient) distributions across the entire chip under a set of local and global workload (power density) constraints. To address the computational challenges introduced by the large 3D mesh-structured thermal grids, we propose a novel spectral approach for highly-scalable vectorless thermal verification of large chip designs. Our approach is based on emerging spectral graph theory and graph signal processing techniques, which consists of a thermal grid topology sparsification phase, an edge weight scaling phase, as well as a solution refinement procedure. The effectiveness and efficiency of our approach have been demonstrated through extensive experiments.
AB - Existing chip thermal analysis and verification methods require detailed distribution of power densities or modeling of underlying input workloads (vectors), which may not always be feasible at early-design stage. This paper introduces the first vectorless thermal integrity verification framework that allows computing worst-case temperature (gradient) distributions across the entire chip under a set of local and global workload (power density) constraints. To address the computational challenges introduced by the large 3D mesh-structured thermal grids, we propose a novel spectral approach for highly-scalable vectorless thermal verification of large chip designs. Our approach is based on emerging spectral graph theory and graph signal processing techniques, which consists of a thermal grid topology sparsification phase, an edge weight scaling phase, as well as a solution refinement procedure. The effectiveness and efficiency of our approach have been demonstrated through extensive experiments.
KW - algebraic multigrid
KW - spectral graph sparsification
KW - vectorless verification
UR - http://www.scopus.com/inward/record.url?scp=85087417319&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85087417319&partnerID=8YFLogxK
U2 - 10.23919/DATE48585.2020.9116438
DO - 10.23919/DATE48585.2020.9116438
M3 - Conference contribution
AN - SCOPUS:85087417319
T3 - Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
SP - 412
EP - 417
BT - Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
A2 - Di Natale, Giorgio
A2 - Bolchini, Cristiana
A2 - Vatajelu, Elena-Ioana
T2 - 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
Y2 - 9 March 2020 through 13 March 2020
ER -