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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20181221T160728Z
LOCATION:D161
DTSTART;TZID=America/Chicago:20181112T171000
DTEND;TZID=America/Chicago:20181112T173000
UID:submissions.supercomputing.org_SC18_sess158_ws_lasalss117@linklings.co
 m
SUMMARY:On Advanced Monte Carlo Methods for Linear Algebra on Advanced Acc
 elerator Architectures
DESCRIPTION:Workshop\nAlgorithms, Heterogeneous Systems, Resiliency, Works
 hop Reg Pass\n\nOn Advanced Monte Carlo Methods for Linear Algebra on Adva
 nced Accelerator Architectures\n\nLebedev, Alexandrov\n\nIn this paper we 
 present computational experiments performed using the Markov Chain Monte C
 arlo Matrix Inversion (MCMCMI) on several architectures of NVIDIA accelera
 tors and two iterations of the Intel x86 architecture and investigate thei
 r impact on performance and scalability of the method.\nThe method is used
  as a preconditioner and iterative methods, such as generalized minimal re
 siduals (GMRES) or bi-conjugate gradient stabilized (BICGstab), are used f
 or solving the corresponding system of linear equations.\nNumerical experi
 ments are carried out to highlight the benefits and deficiencies of both a
 rchitecture types and to assess their overall usefulness in light of the s
 calability of the method.
URL:https://sc18.supercomputing.org/presentation/?id=ws_lasalss117&sess=se
 ss158
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