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DTSTART:19700308T020000
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DTSTAMP:20181221T160726Z
LOCATION:D221
DTSTART;TZID=America/Chicago:20181111T145100
DTEND;TZID=America/Chicago:20181111T151100
UID:submissions.supercomputing.org_SC18_sess162_ws_cre104@linklings.com
SUMMARY:High Performance Implementation of Reproducible BLAS Routines with
  Tunable Accuracy Using Ozaki Scheme
DESCRIPTION:Workshop\nExascale, Hot Topics, Reproducibility, Scientific Co
 mputing, Workshop Reg Pass\n\nHigh Performance Implementation of Reproduci
 ble BLAS Routines with Tunable Accuracy Using Ozaki Scheme\n\nMukunoki, Og
 ita, Ozaki\n\nThis study presents a high performance implementation of Bas
 ic Linear Algebra Subprograms (BLAS) routines supporting reproducibility a
 nd tunable accuracy using the Ozaki scheme, which is an accurate matrix-mu
 ltiplication method proposed by Ozaki et al. in 2011. The method ensures r
 eproducibility and realizes tunable accuracy, including correct-rounding, 
 by eliminating the effect of rounding-error in the computation. The most a
 dvantage of the method is that the method can be constructed based on leve
 l-3 BLAS. In this study, we show the implementation of three routines from
  level 1-3 BLAS: inner-product (DOT), matrix-vector multiplication (GEMV),
  and matrix-matrix multiplication (GEMM), with several optimization techni
 ques for reducing the memory consumption and improving the performance. Th
 e performance evaluation on Titan V GPU demonstrates that our implementati
 on achieves more than 73% of the expected peak performance.
URL:https://sc18.supercomputing.org/presentation/?id=ws_cre104&sess=sess16
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