JSIAM Letters
Online ISSN : 1883-0617
Print ISSN : 1883-0609
ISSN-L : 1883-0617
Performance prediction of massively parallel computation by Bayesian inference
Hisashi KohashiHarumichi IwamotoTakeshi FukayaYusaku YamamotoTakeo Hoshi
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2022 Volume 14 Pages 13-16

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Abstract

A performance prediction method for massively parallel computation is proposed. The method is based on performance modeling and Bayesian inference to predict elapsed time $T$ as a function of the number of used nodes $P$ ($T=T(P)$). The focus is on extrapolation for larger values of $P$ from the perspective of application researchers. The proposed method has several improvements over the method developed in a previous paper, and application to real-symmetric generalized eigenvalue problem shows promising prediction results. The method is generalizable and applicable to many other computations.

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© 2022, The Japan Society for Industrial and Applied Mathematics
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