Matches in SemOpenAlex for { <https://semopenalex.org/work/W2786013445> ?p ?o ?g. }
- W2786013445 endingPage "936" @default.
- W2786013445 startingPage "893" @default.
- W2786013445 abstract "While modern parallel computing systems offer high performance, utilizing these powerful computing resources to the highest possible extent demands advanced knowledge of various hardware architectures and parallel programming models. Furthermore, optimized software execution on parallel computing systems demands consideration of many parameters at compile-time and run-time. Determining the optimal set of parameters in a given execution context is a complex task, and therefore to address this issue researchers have proposed different approaches that use heuristic search or machine learning. In this paper, we undertake a systematic literature review to aggregate, analyze and classify the existing software optimization methods for parallel computing systems. We review approaches that use machine learning or meta-heuristics for software optimization at compile-time and run-time. Additionally, we discuss challenges and future research directions. The results of this study may help to better understand the state-of-the-art techniques that use machine learning and meta-heuristics to deal with the complexity of software optimization for parallel computing systems. Furthermore, it may aid in understanding the limitations of existing approaches and identification of areas for improvement." @default.
- W2786013445 created "2018-02-23" @default.
- W2786013445 creator A5004409444 @default.
- W2786013445 creator A5009158531 @default.
- W2786013445 creator A5021961745 @default.
- W2786013445 creator A5041301604 @default.
- W2786013445 creator A5066530334 @default.
- W2786013445 date "2018-04-26" @default.
- W2786013445 modified "2023-09-30" @default.
- W2786013445 title "Using meta-heuristics and machine learning for software optimization of parallel computing systems: a systematic literature review" @default.
- W2786013445 cites W102800333 @default.
- W2786013445 cites W142211077 @default.
- W2786013445 cites W1483717008 @default.
- W2786013445 cites W1538074505 @default.
- W2786013445 cites W1803140274 @default.
- W2786013445 cites W1803549484 @default.
- W2786013445 cites W1805440014 @default.
- W2786013445 cites W1817724761 @default.
- W2786013445 cites W1864199185 @default.
- W2786013445 cites W1967159579 @default.
- W2786013445 cites W1967846636 @default.
- W2786013445 cites W1977367431 @default.
- W2786013445 cites W1978959587 @default.
- W2786013445 cites W1984222112 @default.
- W2786013445 cites W1990262300 @default.
- W2786013445 cites W1991591392 @default.
- W2786013445 cites W2010970156 @default.
- W2786013445 cites W2022991653 @default.
- W2786013445 cites W2025397485 @default.
- W2786013445 cites W2029282088 @default.
- W2786013445 cites W2053341340 @default.
- W2786013445 cites W2056579078 @default.
- W2786013445 cites W2058340614 @default.
- W2786013445 cites W2058826126 @default.
- W2786013445 cites W2060533244 @default.
- W2786013445 cites W2083304636 @default.
- W2786013445 cites W2089948839 @default.
- W2786013445 cites W2112340065 @default.
- W2786013445 cites W2118937112 @default.
- W2786013445 cites W2122607012 @default.
- W2786013445 cites W2125771852 @default.
- W2786013445 cites W2129298093 @default.
- W2786013445 cites W2132218691 @default.
- W2786013445 cites W2136202858 @default.
- W2786013445 cites W2137311321 @default.
- W2786013445 cites W2137788104 @default.
- W2786013445 cites W2140707050 @default.
- W2786013445 cites W2141179376 @default.
- W2786013445 cites W2142079700 @default.
- W2786013445 cites W2145771636 @default.
- W2786013445 cites W2146757372 @default.
- W2786013445 cites W2149236908 @default.
- W2786013445 cites W2150476673 @default.
- W2786013445 cites W2154158105 @default.
- W2786013445 cites W2156560068 @default.
- W2786013445 cites W2158322839 @default.
- W2786013445 cites W2158626113 @default.
- W2786013445 cites W2160241055 @default.
- W2786013445 cites W2163109311 @default.
- W2786013445 cites W2165100134 @default.
- W2786013445 cites W2165504557 @default.
- W2786013445 cites W2168519934 @default.
- W2786013445 cites W2171892642 @default.
- W2786013445 cites W2417987166 @default.
- W2786013445 cites W2466307858 @default.
- W2786013445 cites W2512238070 @default.
- W2786013445 cites W2540559162 @default.
- W2786013445 cites W2578922287 @default.
- W2786013445 cites W2594987874 @default.
- W2786013445 cites W2604520782 @default.
- W2786013445 cites W2612954225 @default.
- W2786013445 cites W288065879 @default.
- W2786013445 cites W2963916453 @default.
- W2786013445 cites W2998249817 @default.
- W2786013445 cites W3146774908 @default.
- W2786013445 cites W4241729224 @default.
- W2786013445 cites W59960346 @default.
- W2786013445 cites W2046505282 @default.
- W2786013445 doi "https://doi.org/10.1007/s00607-018-0614-9" @default.
- W2786013445 hasPublicationYear "2018" @default.
- W2786013445 type Work @default.
- W2786013445 sameAs 2786013445 @default.
- W2786013445 citedByCount "38" @default.
- W2786013445 countsByYear W27860134452018 @default.
- W2786013445 countsByYear W27860134452019 @default.
- W2786013445 countsByYear W27860134452020 @default.
- W2786013445 countsByYear W27860134452021 @default.
- W2786013445 countsByYear W27860134452022 @default.
- W2786013445 countsByYear W27860134452023 @default.
- W2786013445 crossrefType "journal-article" @default.
- W2786013445 hasAuthorship W2786013445A5004409444 @default.
- W2786013445 hasAuthorship W2786013445A5009158531 @default.
- W2786013445 hasAuthorship W2786013445A5021961745 @default.
- W2786013445 hasAuthorship W2786013445A5041301604 @default.
- W2786013445 hasAuthorship W2786013445A5066530334 @default.
- W2786013445 hasBestOaLocation W27860134451 @default.
- W2786013445 hasConcept C111919701 @default.
- W2786013445 hasConcept C115903868 @default.