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DTSTAMP:20210402T160550Z
LOCATION:Poster Module
DTSTART;TZID=America/New_York:20201119T083000
DTEND;TZID=America/New_York:20201119T170000
UID:submissions.supercomputing.org_SC20_sess341_spostu118@linklings.com
SUMMARY:Randomized Cholesky Factorization in Parallel
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nRandomized Cholesk
 y Factorization in Parallel\n\nLiang\n\nLarge sparse SDD (symmetric diagon
 ally dominant) linear systems arise from solving elliptic PDEs and graph p
 roblems. Exact Cholesky factorization leads to excessive fill-in, especial
 ly in 3D. Our approach is to subsample the (dense) Schur complement update
  and construct an (approximate) sparse preconditioner. To optimize for pra
 ctical performance, we reorder the original matrix to exploit the sparsity
  pattern. In particular, we apply a log(P)-level nested dissection followe
 d by AMD (approximate minimum degree) ordering at the leaf level, where P 
 is the number of threads. This ordering naturally leads to a parallel meth
 od. Results show that our preconditioner outperformed standard incomplete 
 Cholesky preconditioner with much less iterations and scaled up to 64 thre
 ads on a multicore CPU. Our poster has three major parts: the randomized s
 ampling algorithm, the parallel algorithm/implementation, and results on p
 arallel scalability as well as comparison to incomplete Cholesky.\n\nTag: 
 Student Program\n\nRegistration Category: Tech Program Reg Pass, Exhibits 
 Reg Pass
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