DocumentCode :
507408
Title :
Taming irregular EDA applications on GPUs
Author :
Yangdong Deng ; Wang, B.D. ; Shuai Mu
Author_Institution :
Inst. of Microelectron., Tsinghua Univ., Beijing, China
fYear :
2009
fDate :
2-5 Nov. 2009
Firstpage :
539
Lastpage :
546
Abstract :
Recently general purpose computing on graphic processing units (GPUs) is rising as an exciting new trend in high-performance computing. Thus it is appealing to study the potential of GPU for Electronic Design Automation (EDA) applications. However, EDA generally involves irregular data structures such as sparse matrix and graph operations, which pose significant challenges for efficient GPU implementations. In this paper, we propose high-performance GPU implementations for two important irregular EDA computing patterns, Sparse-Matrix Vector Product (SMVP) and graph traversal. On a wide range of EDA problem instances, our SMVP implementations outperform all published work and achieve a speedup of one order of magnitude over the CPU baseline. Upon such a basis, both timing analysis and linear system solution can be considerably accelerated. We also introduce a SMVP based formulation for Breadth-First Search and observe considerable speedup on GPU implementations. Our results suggest that the power of GPU computing can be successfully unleashed through designing GPU-friendly algorithms and/or re-organizing computing structures of current algorithms.
Keywords :
electronic design automation; graph grammars; parallel programming; sparse matrices; GPU; breadth-first search; electronic design automation; graph operations; graph traversal; graphic processing units; high-performance computing; irregular EDA applications; irregular data structures; sparse-matrix vector product; Acceleration; Algorithm design and analysis; Central Processing Unit; Data structures; Electronic design automation and methodology; Graphics; Linear systems; Sparse matrices; Timing; Vectors; CUDA; EDA; GPU; breadth-first search; conjugate gradient; data parallel computing; graph algorithms; placement; sparse matrix; sparse-matrix vector product; static timing analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Aided Design - Digest of Technical Papers, 2009. ICCAD 2009. IEEE/ACM International Conference on
Conference_Location :
San Jose, CA
ISSN :
1092-3152
Print_ISBN :
978-1-60558-800-1
Type :
conf
Filename :
5361242
Link To Document :
بازگشت