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Title:
performance evaluation of multithreaded sparse matrix-vector multiplication using openmp
Author: Liu Shengfei ; Zhang Yunquan ; Sun Xiangzheng ; Qiu RongRong
Source: 2009 11th IEEE International Conference on High Performance Computing and Communications, HPCC 2009
Conference Name: 11th IEEE International Conference on High Performance Computing and Communications
Conference Date: JUN 25-27,
Issued Date: 2009
Conference Place: Seoul, SOUTH KOREA
Keyword: Dawning S4800A1 ; OpenMP ; compute-to-memory ratio ; irregular memory access patterns ; iterative methods ; multithreaded sparse matrix-vector multiplication ; nonzero scheduling ; performance evaluation ; application program interfaces ; matrix multiplication ; multi-threading ; scheduling ; shared memory systems ; software performance evaluation ; sparse matrices ; vectors
Publisher: HPCC: 2009 11TH IEEE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS
Publish Place: 345 E 47TH ST, NEW YORK, NY 10017 USA
ISBN: 978-1-4244-4600-1
Department: Liu, Shengfei; Zhang, Yunquan; Sun, Xiangzheng Chinese Acad Sci, Inst Software, Beijing 100864, Peoples R China.
Sponsorship: IEEE Comp Soc, IEEE
English Abstract: Sparse matrix-vector multiplication is an important computational kernel in scientific applications. However, it performs poorly on modern processors because of a low compute-to-memory ratio and its irregular memory access patterns. This paper discusses the implementations of sparse matrix-vector algorithm using OpenMP to execute iterative methods on the Dawning S4800A1. Two storage formats (CSR and BCSR) for sparse matrices and three scheduling schemes (static, dynamic and guided) provided by the standard OpenMP are evaluated We also compared these three schemes with non-zero scheduling, where each thread is assigned approximately the same number of non-zero elements. Experimental data shows that, the non-zero scheduling can provide the best performance in most cases. The current implementation provides satisfactory scalability for most of matrices. However, we only get a limited speedup for some large matrices that contain millions of non-zero elements.
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/8288
Appears in Collections:并行计算实验室 _会议论文

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Recommended Citation:
Liu Shengfei,Zhang Yunquan,Sun Xiangzheng,et al. performance evaluation of multithreaded sparse matrix-vector multiplication using openmp[C]. 见:11th IEEE International Conference on High Performance Computing and Communications. Seoul, SOUTH KOREA. JUN 25-27,.
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