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DTSTAMP:20211207T055352Z
LOCATION:220-221
DTSTART;TZID=America/Chicago:20211118T103000
DTEND;TZID=America/Chicago:20211118T120000
UID:submissions.supercomputing.org_SC21_sess161@linklings.com
SUMMARY:Linear and Multilinear Algebra and Applications
DESCRIPTION:Paper\n\nSTM-Multifrontal QR: Streaming Task Mapping Multifron
 tal QR Factorization Empowered by GCN\n\nLin, Yang, Wang, Tsai, Li\n\nMult
 ifrontal QR algorithm, which consists of symbolic analysis and numerical f
 actorization, is a high-performance algorithm for orthogonal factorizing s
 parse matrix. In this work, a graph convolutional network (GCN) for adapti
 vely selecting the optimal reordering algorithm is proposed in symbolic an
 ...\n\n---------------------\nLibShalom: Optimizing Small and Irregular-Sh
 aped Matrix Multiplications on ARMv8 Multi-Cores\n\nYang, Fang, Dong, Su, 
 Wang\n\nGeneral matrix multiplication (GEMM) is a key subroutine in high-p
 erformance computing. While the existing BLAS libraries can obtain near pe
 ak hardware performance on large GEMM, they deliver low performance on sma
 ll and irregularly-shaped GEMM. We propose and implement an algorithm for 
 small and ir...\n\n---------------------\nOn the Parallel I/O Optimality o
 f Linear Algebra Kernels:  Near-Optimal Matrix Factorizations\n\nKwasniews
 ki, Kabić, Ben-Nun, Ziogas, Saethre...\n\nMatrix factorizations are a
 mong the most important building blocks of scientific computing. State-of-
 the-art libraries, however, are not communication-optimal, underutilizing 
 current parallel architectures. We present novel algorithms for Cholesky a
 nd LU factorizations that utilize an asymptotically...\n\n\nTag: Algorithm
 s, Architectures, Numerical Algorithms\n\nRegistration Category: Tech Prog
 ram Reg Pass
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