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Thursday, March 3 • 11:50am - 12:10pm
Algorithms & Accelerators II: A Survey of Sparse Matrix-Vector Multiple Performance on Large Matrices

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Iterative linear solvers are popular in large-scale
computing as they consume less memory than direct solvers.
Contrary to direct linear solvers, iterative solvers approach the
solution gradually requiring the computation of sparse matrix-
vector (SpMV) products. The evaluation of SpMV products
can emerge as a bottleneck for computational performance
within the context of the simulation of large problems. In this
work, we focus on a linear system arising from the discretiza-
tion of the Cahn{Hilliard equation, which is a fourth order non-
linear parabolic partial differential equation that governs the
separation of a two-component mixture into phases [3]. The
underlying spatial discretization is performed using the dis-
continuous Galerkin method and Newton's method.
A number of parallel algorithms and strategies have been eval-
uated in this work to accelerate the evaluation of SpMV prod-
ucts. “


Mauricio Araya

Senior Researcher Computer Science, Shell Intl. E&P Inc.

Florian Frank

Rice University

Thursday March 3, 2016 11:50am - 12:10pm
BioScience Research Collaborative Building (BRC), Room 280 & 282

Attendees (3)