SCHEDULE: NOV 15-20, 2015

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Analyzing the Performance of a Sparse Matrix Vector Multiply for Extreme Scale Computers

SESSION: Regular & ACM Student Research Competition Poster Reception

EVENT TYPE: Posters, Receptions, ACM Student Research Competition

EVENT TAG(S): HPC Beginner Friendly, Regular Poster

TIME: 5:15PM - 7:00PM

SESSION CHAIR(S): Michela Becchi, Manish Parashar, Dorian C. Arnold

AUTHOR(S):Amanda Bienz, Jon Calhoun, Luke Olson, Marc Snir, William D. Gropp

ROOM:Level 4 - Lobby

ABSTRACT:

As high-performance computing systems continue to progress towards extreme scale, the scalability
of 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
SpMV routines in the widely used software
packages 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.

Chair/Author Details:

Michela Becchi, Manish Parashar, Dorian C. Arnold (Chair) - University of Missouri|Rutgers University|University of New Mexico|

Amanda Bienz - University of Illinois at Urbana-Champaign

Jon Calhoun - University of Illinois at Urbana-Champaign

Luke Olson - University of Illinois at Urbana-Champaign

Marc Snir - University of Illinois at Urbana-Champaign

William D. Gropp - University of Illinois at Urbana-Champaign

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