Performance evaluation of parallel sparse matrix-vector products on SGI Altix3700

  • Authors:

  • Hisashi Kotakemori;Hidehiko Hasegawa;Tamito Kajiyama;Akira Nukada;Reiji Suda;Akira Nishida

  • Affiliations:

  • CREST, Japan Science and Technology Agency, Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan;CREST, Japan Science and Technology Agency, Graduate School of Library, Information and Media Studies, University of Tsukuba, Tsukuba, Japan;CREST, Japan Science and Technology Agency, Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan;CREST, Japan Science and Technology Agency, Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan;CREST, Japan Science and Technology Agency, Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan;CREST, Japan Science and Technology Agency, Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan

  • Venue:
  • IWOMP'05/IWOMP'06 Proceedings of the 2005 and 2006 international conference on OpenMP shared memory parallel programming
  • Year:
  • 2005

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Abstract

The present paper discusses scalable implementations of sparse matrix-vector products, which are crucial for high performance solutions of large-scale linear equations, on a cc-NUMA machine SGI Altix3700. Three storage formats for sparse matrices are evaluated, and scalability is attained by implementations considering the page allocation mechanism of the NUMA machine. Influences of the cache/memory bus architectures on the optimum choice of the storage format are examined, and scalable converters between storage formats shown to facilitate exploitation of storage formats of higher performance.