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Parallel software auto-tuning using statistical modeling and machine learning

Auto-tuning for complex and nontrivial parallel systems is usually time-consuming because of empirical evaluation of huge amount of combinations of parameter values of an initial parallel program in a target execution environment. This paper proposes the improvement of the auto-tuning method using s...

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Bibliographic Details
Date:	2018
Main Authors:	Doroshenko, А.Yu., Ivanenko, P.A., Novak, O.S., Yatsenko, O.A.
Format:	Article
Language:	Ukrainian
Published:	PROBLEMS IN PROGRAMMING 2018
Subjects:	auto-tuning software development automation machine learning neural network parallel computing statistical modeling UDC 004.4'24
Online Access:	https://pp.isofts.kiev.ua/index.php/ojs1/article/view/264
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Journal Title:	Problems in programming
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