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.

翻译：提出了大规模平行计算性能预测方法,其依据是性能建模和贝叶斯推论,根据使用节点P(T=T(P))的数量来预测时间的流逝时间(T=T(P)),重点是从应用研究人员的角度推断P的较大值,拟议方法比前一份文件制定的方法有几项改进,对实际对称通用电子价值问题的应用显示了有希望的预测结果。该方法可普遍适用,适用于许多其他计算方法。