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Fast and memory-efficient GPU implementations of krylov subspace methods for efficient power grid analysis

Published: 02 May 2013 Publication History
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  • Abstract

    Power grid analysis for modern LSI is computationally challenging in terms of both runtime and memory usage. In this paper, we implement Krylov subspace based linear circuit solvers on a graphics processing unit (GPU) to realize fast power grid analysis. Efficiencies of memory space and access performance are pursued by improving a data structure that stores elements of large sparse matrices. Experimental results on benchmark circuits show that the proposed data structures are more suitable than widely used compressed sparse row (CSR) format and our GPU implementations can achieve up to 17x speedup over CPU implementations.

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    Cited By

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    • (2017)Markov Chain Model Using Lévy Flight for VLSI Power Grid Analysis2017 30th International Conference on VLSI Design and 2017 16th International Conference on Embedded Systems (VLSID)10.1109/VLSID.2017.8(107-112)Online publication date: Jan-2017
    • (2016)Applying River Formation Dynamics to Analyze VLSI Power Grid NetworksProceedings of the 2016 29th International Conference on VLSI Design and 2016 15th International Conference on Embedded Systems (VLSID)10.1109/VLSID.2016.42(258-263)Online publication date: 4-Jan-2016
    • (2015)Power grid analysis on parallel computing platforms2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA)10.1109/RADIOELEK.2015.7129061(89-93)Online publication date: Apr-2015
    • Show More Cited By

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    Published In

    cover image ACM Conferences
    GLSVLSI '13: Proceedings of the 23rd ACM international conference on Great lakes symposium on VLSI
    May 2013
    368 pages
    ISBN:9781450320320
    DOI:10.1145/2483028
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 02 May 2013

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    Author Tags

    1. gpgpu
    2. krylov subspace method
    3. power grid analysis

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    GLSVLSI '13 Paper Acceptance Rate 76 of 238 submissions, 32%;
    Overall Acceptance Rate 312 of 1,156 submissions, 27%

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    • (2017)Markov Chain Model Using Lévy Flight for VLSI Power Grid Analysis2017 30th International Conference on VLSI Design and 2017 16th International Conference on Embedded Systems (VLSID)10.1109/VLSID.2017.8(107-112)Online publication date: Jan-2017
    • (2016)Applying River Formation Dynamics to Analyze VLSI Power Grid NetworksProceedings of the 2016 29th International Conference on VLSI Design and 2016 15th International Conference on Embedded Systems (VLSID)10.1109/VLSID.2016.42(258-263)Online publication date: 4-Jan-2016
    • (2015)Power grid analysis on parallel computing platforms2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA)10.1109/RADIOELEK.2015.7129061(89-93)Online publication date: Apr-2015
    • (2015)Parallel two step random walk algorithm to analyze VLSI power grid networks2015 19th International Symposium on VLSI Design and Test10.1109/ISVDAT.2015.7208101(1-2)Online publication date: Jun-2015

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