We consider performance tuning by code and data structure reorganization, of sparse matrix-vector multiply (SpMxV), one of the most important computational kernels in scientific applications. This paper addresses the fundamental questions of what limits exist on such performance tuning, and how closely tuned code approaches these limits.

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In: Supercomputing 2002

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