BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Sherry Li (Lawrence Berkeley National Laboratory) DTSTART:20201014T140000Z DTEND:20201014T150000Z DTSTAMP:20260423T041611Z UID:E-NLA/18 DESCRIPTION:Title: A utotuning exascale applications with Gaussian process regression\nby S herry Li (Lawrence Berkeley National Laboratory) as part of E-NLA - Online seminar series on numerical linear algebra\n\n\nAbstract\nSignificant eff ort has been invested to develop highly scalable numerical libraries and h igh-fidelity modeling and simulation for the upcoming exascale computers. These codes typically involve many parameters which need to be selected pr operly to optimize performance on the underlying parallel machine. They ar e also expensive to run and thus have limited "function evaluation" values \, which post significant challenges to efficient performance tuning on di verse architectures.\n\nBayesian optimization with Gaussian process regres sion is an attractive machine learning framework to build surrogate models with limited function evaluation points. In order to fully utilize all th e available data\, we leverage multitask learning and multi-armed bandit s trategies to build a more advanced Bayesian optimization framework.\n\nWe have developed an open-source software tool\, called GPTune\, for optimizi ng expensive large-scale HPC codes. We will show several features of GPTun e\, e.g.\, incorporation of coarse performance models to improve the Bayes ian model\, multi-objective tuning such as tuning a hybrid of time\, memor y and accuracy\, and reuse of historical data base for model portability.\ n\nWe will demonstrate the efficiency and effectiveness of GPTune when it is applied to numerical linear algebra libraries\, such as ScaLAPACK\, Sup erLU and Hypre\, as well as fusion simulation codes M3D-C1 and NIMROD.\n\n This talk describes joint work with James Demmel\, Yang Liu\, Osni Marques \, Wissam Sid-Lakhdar and Xianran Zhu\n LOCATION:https://researchseminars.org/talk/E-NLA/18/ END:VEVENT END:VCALENDAR