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DTSTART:19700308T020000
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DTSTAMP:20181221T160731Z
LOCATION:C141/143/149
DTSTART;TZID=America/Chicago:20181115T110000
DTEND;TZID=America/Chicago:20181115T113000
UID:submissions.supercomputing.org_SC18_sess207_pap256@linklings.com
SUMMARY:ParSy: Inspection and Transformation of Sparse Matrix Computations
  for Parallelism
DESCRIPTION:Paper\nLinear Algebra, Memory, MPI, OpenMP, Programming System
 s, Tools, Tech Program Reg Pass\n\nParSy: Inspection and Transformation of
  Sparse Matrix Computations for Parallelism\n\nCheshmi, Kamil, Mills Strou
 t, Mehri Dehnavi\n\nIn this work, we describe ParSy, a framework that uses
  a novel inspection strategy along with a simple code transformation to op
 timize parallel sparse algorithms for shared memory processors. Unlike exi
 sting approaches that can suffer from load imbalance and excessive synchro
 nization, ParSy uses a novel task coarsening strategy to create well-balan
 ced tasks that can execute in parallel, while maintaining locality of memo
 ry accesses. Code using the ParSy inspector and transformation outperforms
  existing highly-optimized sparse matrix algorithms such as Cholesky facto
 rization on multi-core processors with speedups of 2.8× and 3.1× over the 
 MKL Pardiso and PaStiX libraries respectively.
URL:https://sc18.supercomputing.org/presentation/?id=pap256&sess=sess207
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