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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20210402T160555Z
LOCATION:Track 8
DTSTART;TZID=America/New_York:20201112T110000
DTEND;TZID=America/New_York:20201112T112500
UID:submissions.supercomputing.org_SC20_sess214_ws_lasalss104@linklings.co
 m
SUMMARY:An Integer Arithmetic-Based Sparse Linear Solver Using a GMRES Met
 hod and Iterative Refinement
DESCRIPTION:Workshop\n\nAn Integer Arithmetic-Based Sparse Linear Solver U
 sing a GMRES Method and Iterative Refinement\n\nIwashita, Suzuki, Fukaya\n
 \nIn this paper, we develop a (preconditioned) GMRES solver based on integ
 er arithmetic, and introduce an iterative refinement framework for the sol
 ver. We describe the data format for the coefficient matrix and vectors fo
 r the solver that is based on integer or fixed-point numbers.\nTo avoid ov
 erflow in calculations, we introduce initial scaling and logical shifts (a
 djustments) of operands in arithmetic operations. We present the approach 
 operand shifts, considering the characteristics of the GMRES algorithm. Nu
 merical tests demonstrate that the integer arithmetic-based solver with it
 erative refinement has comparable solver performance in terms of convergen
 ce to the standard solver based on floating-point arithmetic. Moreover, we
  show that preconditioning is important, not only for improving convergenc
 e but also reducing the risk of overflow.\n\nTag: Algorithms, Extreme Scal
 e Computing, Performance/Productivity Measurement and Evaluation, Scalable
  Computing, Scientific Computing\n\nRegistration Category: Workshop Reg Pa
 ss
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