Performance prediction of massively parallel computation by Bayesian inference

抄録

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.