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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
VERSION:2.0
BEGIN:VEVENT
DTSTART:20151117T231500Z
DTEND:20151118T010000Z
LOCATION:Level 4 - Lobby
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: As high-performance computing systems continue to progress towards extreme scale, the scalability=0Aof applications becomes critical. The scalability of an algorithm is dependent on interconnect properties, such as latency and bandwidth, and is often limited by network contention.  Sparse matrix-vector multiplication (SpMV) is fundamental to a large class of HPC applications. We investigate the performance and scalability of=0ASpMV routines in the widely used software=0Apackages PETSc, Hypre, and Trilinos.  Through the use of an asynchronous multiplication, we show an improvement in scalability and performance of the SpMV operation when applied to various matrices.
SUMMARY:Analyzing the Performance of a Sparse Matrix Vector Multiply for Extreme Scale Computers
PRIORITY:3
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