Dynamic GPU Parallel Sparse LU Factorization for Fast Circuit Simulation

Lower-upper (LU) factorization is widely used in many scientific computations. It is one of the most critical modules in circuit simulators, such as the Simulation Program With Integrated Circuit Emphasis. To exploit the emerging graphics process unit (GPU) computing platforms, several GPU-based spa...

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Bibliographic Details
Published in:IEEE transactions on very large scale integration (VLSI) systems Vol. 26; no. 11; pp. 2518 - 2529
Main Authors: Lee, Wai-Kong, Achar, Ramachandra, Nakhla, Michel S.
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Circuit simulation
Computer architecture
Computer simulation
Factorization
graphics processing unit (GPU)
Graphics processing units
Heuristic algorithms
Integrated circuit modeling
Integrated circuits
Kernel
lower–upper (LU) factorization
Mathematical model
multicore
Parallel processing
parallel simulation
Performance assessment
Simulation Program With Integrated Circuit Emphasis (SPICE)
Simulators
Solvers
sparse matrices
State of the art
ISSN:1063-8210, 1557-9999
Online Access:Get full text
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Summary:Lower-upper (LU) factorization is widely used in many scientific computations. It is one of the most critical modules in circuit simulators, such as the Simulation Program With Integrated Circuit Emphasis. To exploit the emerging graphics process unit (GPU) computing platforms, several GPU-based sparse LU solvers have been recently proposed. In this paper, efficient algorithms are presented to enhance the ability of GPU-based LU solvers to achieve higher parallelism as well as to exploit the dynamic parallelism feature in the state-of-the-art GPUs. Also, rigorous performance comparisons of the proposed algorithms with GLU as well as KLU, for both the single-precision and double-precision cases, are presented.
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ISSN:1063-8210
1557-9999
DOI:10.1109/TVLSI.2018.2858014