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LOCATION:DEF Concourse
DTSTART;TZID=America/Denver:20231114T100000
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UID:submissions.supercomputing.org_SC23_sess291_rpost212@linklings.com
SUMMARY:A Hybrid Factorization Solver with Mixed Precision Arithmetic for 
 Sparse Matrices
DESCRIPTION:Atsushi Suzuki (RIKEN Center for Computational Science (R-CCS)
 )\n\nFor numerical simulations, linear system with large sparse matrix wit
 h high condition number needs to be solved. LDU-factorization with pivotin
 g strategy provides robust solver for such system. Computational complexit
 y of the factorization solver is high and cannot be reduced in framework o
 f the direct solver, but by using lower precision arithmetic, computationa
 l cost and memory usage could be reduced. LDU-factorization uses recursive
  generation of the Schur complement matrix, but generation of the last one
  can be replaced by an iterative method. Here decomposition of the whole m
 atrix into a union of the moderate and hard parts during factorization wit
 h threshold pivoting plays a key role. A new algorithm uses factorization 
 in lower precision as a preconditioner for iterative solver in higher prec
 ision to generate the last Schur complement. True mixed precision arithmet
 ic is used in forward/backward substitution for preconditioner with factor
 ized matrix in lower precision and RHS vectors in higher.\n\nTag: Artifici
 al Intelligence/Machine Learning, Architecture and Networks, Heterogeneous
  Computing, I/O and File Systems, Performance Measurement, Modeling, and T
 ools, Post-Moore Computing, Programming Frameworks and System Software, Qu
 antum Computing\n\nRegistration Category: Tech Program Reg Pass, Exhibits 
 Reg Pass\n\n
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