Experience with fine-grain communication in EM-X multiprocessor for parallel sparse matrix computation

Mitsuhisa Sato*, Yuetsu Kodama, Hirofumi Sakane, Hayato Yamana, Shuichi Sakai, Yoshinori Yamaguchi

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


Sparse matrix problems require a communication paradigm different from those used in conventional distributed-memory multiprocessors. We present in this paper how fine-grain communication can help obtain high performance in the experimental distributed-memory multiprocessor, EM-X, developed at ETL, which can handle fine-grain communication very efficiently. The sparse matrix kernel, Conjugate Gradient, is selected for the experiments. Among the steps in CG is the sparse matrix vector multiplications we focus on in the study. Some communication methods are developed for performance comparison, including coarse-grain and fine-grain implementations. Fine-grain communication allows exact data access in an unstructured problem to reduce the amount of communication. While CG presents bottlenecks in terms of a large number of fine-grain remote reads, the multithreaded principles of execution is so designed to tolerate such latency. Experimental results indicate that the performance of fine-grain read implementation is comparable to that of coarse-grain implementation on 64 processors. The results demonstrate that fine-grain communication can be a viable and efficient approach to unstructured sparse matrix problems on large-scale distributed-memory multiprocessors.

Original languageEnglish
Pages (from-to)242-248
Number of pages7
JournalProceedings of the International Parallel Processing Symposium, IPPS
Publication statusPublished - 1997 Jan 1
Externally publishedYes
EventProceedings of the 1997 11th International Parallel Processing Symposium, IPPS 97 - Geneva, Switz
Duration: 1997 Apr 11997 Apr 5

ASJC Scopus subject areas

  • Hardware and Architecture


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