Mohammadi, Seyed Ali ; Rothenberger, Lukas ; Morais, Gustavo de ; Görlich, Bertin Nico ; Lille, Erik ; Rüthers, Hendrik ; Wolf, Felix (2023)
Filtering and Ranking of Code Regions for Parallelization via Hotspot Detection and OpenMP Overhead Analysis.
2023 International Conference on High Performance Computing, Network, Storage, and Analysis. Denver, USA (12.-17.11.2023)
doi: 10.1145/3624062.3624206
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Many high-performance computing applications reach millions of code lines and hundreds of code regions. Analyzing all code regions for parallelization with OpenMP is neither efficient nor necessary. To facilitate this task and minimize the effort by the user, the code regions of the application need to be filtered and ranked. We provide a simple filtering method to detect the critical code regions by clearly defining a hotspot. Afterward, we identify parallelizable loops by analyzing their data dependencies using an automatic tool. As the number of parallel opportunities can be high and the users must verify these parallel suggestions, we suggest a ranking strategy based on parallelization overhead to help them prioritize their endeavors and present a set of OpenMP microbenchmarks for overhead analysis. We calculate optimistic expected benefits using overhead estimations as ranking metrics and show how our ranking provides an improvement on the ranking based on serial runtime.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Mohammadi, Seyed Ali ; Rothenberger, Lukas ; Morais, Gustavo de ; Görlich, Bertin Nico ; Lille, Erik ; Rüthers, Hendrik ; Wolf, Felix |
| Art des Eintrags: | Bibliographie |
| Titel: | Filtering and Ranking of Code Regions for Parallelization via Hotspot Detection and OpenMP Overhead Analysis |
| Sprache: | Englisch |
| Publikationsjahr: | 12 November 2023 |
| Verlag: | ACM |
| Buchtitel: | Proceedings of 2023 SC 23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC23Workshops) |
| Reihe: | SC-W '23 |
| Veranstaltungstitel: | 2023 International Conference on High Performance Computing, Network, Storage, and Analysis |
| Veranstaltungsort: | Denver, USA |
| Veranstaltungsdatum: | 12.-17.11.2023 |
| DOI: | 10.1145/3624062.3624206 |
| Kurzbeschreibung (Abstract): | Many high-performance computing applications reach millions of code lines and hundreds of code regions. Analyzing all code regions for parallelization with OpenMP is neither efficient nor necessary. To facilitate this task and minimize the effort by the user, the code regions of the application need to be filtered and ranked. We provide a simple filtering method to detect the critical code regions by clearly defining a hotspot. Afterward, we identify parallelizable loops by analyzing their data dependencies using an automatic tool. As the number of parallel opportunities can be high and the users must verify these parallel suggestions, we suggest a ranking strategy based on parallelization overhead to help them prioritize their endeavors and present a set of OpenMP microbenchmarks for overhead analysis. We calculate optimistic expected benefits using overhead estimations as ranking metrics and show how our ranking provides an improvement on the ranking based on serial runtime. |
| Freie Schlagworte: | BMBF/HMWK|NHR4CES |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Parallele Programmierung |
| Hinterlegungsdatum: | 13 Feb 2024 15:40 |
| Letzte Änderung: | 04 Apr 2024 09:00 |
| PPN: | 516064754 |
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| Suche nach Titel in: | TUfind oder in Google |
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