Atre, Rohit ; Jannesari, Ali ; Wolf, Felix (2017)
Meeting the challenges of parallelizing sequential programs.
29th ACM Symposium on Parallelism in Algorithms and Architectures. Washington DC., USA (24.-26.07.2017)
doi: 10.1145/3087556.3087592
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Discovering which code sections in a sequential program can be made to run in parallel is the first step in parallelizing it, and programmers routinely struggle in this step. Most of the current parallelism discovery techniques focus on specific language constructs while trying to identify such code sections. In contrast, we propose to concentrate on the computations performed by a program. In our approach, a program is treated as a collection of computations communicating with one another using a number of variables. Each computation is represented as a Computational Unit (CU). A CU contains the inputs and outputs of a computation, and the three phases of a computation: read, compute, and write. Based on the notion of CU, We present a unified framework to identify both loop and task parallelism in sequential programs.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2017 |
| Autor(en): | Atre, Rohit ; Jannesari, Ali ; Wolf, Felix |
| Art des Eintrags: | Bibliographie |
| Titel: | Meeting the challenges of parallelizing sequential programs |
| Sprache: | Englisch |
| Publikationsjahr: | 24 Juli 2017 |
| Verlag: | ACM |
| Buchtitel: | SPAA '17: Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures |
| Veranstaltungstitel: | 29th ACM Symposium on Parallelism in Algorithms and Architectures |
| Veranstaltungsort: | Washington DC., USA |
| Veranstaltungsdatum: | 24.-26.07.2017 |
| DOI: | 10.1145/3087556.3087592 |
| Kurzbeschreibung (Abstract): | Discovering which code sections in a sequential program can be made to run in parallel is the first step in parallelizing it, and programmers routinely struggle in this step. Most of the current parallelism discovery techniques focus on specific language constructs while trying to identify such code sections. In contrast, we propose to concentrate on the computations performed by a program. In our approach, a program is treated as a collection of computations communicating with one another using a number of variables. Each computation is represented as a Computational Unit (CU). A CU contains the inputs and outputs of a computation, and the three phases of a computation: read, compute, and write. Based on the notion of CU, We present a unified framework to identify both loop and task parallelism in sequential programs. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Parallele Programmierung |
| Hinterlegungsdatum: | 18 Jan 2018 11:42 |
| Letzte Änderung: | 04 Apr 2024 11:41 |
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