HPC Storage Service Autotuning Using Variational- Autoencoder -Guided Asynchronous Bayesian Optimization

Distributed data storage services tailored to specific applications have grown popular in the high-performance computing (HPC) community as a way to address I/O and storage challenges. These services offer a variety of specific interfaces, semantics, and data representations. They also expose many t...

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Vydané v:	Proceedings / IEEE International Conference on Cluster Computing s. 381 - 393
Hlavní autori:	Dorier, Matthieu, Egele, Romain, Balaprakash, Prasanna, Koo, Jaehoon, Madireddy, Sandeep, Ramesh, Srinivasan, Malony, Allen D., Ross, Rob
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.09.2022
Predmet:	Autotuning Bayes methods Bayesian Optimization DeepHyper HPC I/O Mochi Probability distribution Resource management Semantics Storage Supercomputers Systematics Transfer learning
ISSN:	2168-9253
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