Compute units in OpenMP: extensions for heterogeneous parallel programming
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| Názov: | Compute units in OpenMP: extensions for heterogeneous parallel programming |
|---|---|
| Autori: | González Tallada, Marc, Morancho Llena, Enrique |
| Prispievatelia: | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. PM - Programming Models |
| Informácie o vydavateľovi: | John Wiley & sons |
| Rok vydania: | 2024 |
| Zbierka: | Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge |
| Predmety: | Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors, Parallel programming (Computer science), Application program interfaces (Computer software), Graphics processing units, GPUs, Heterogeneous computing, OpenMP, Work distribution, Programació en paral·lel (Informàtica), Interfícies de programació d'aplicacions (Programari), Unitats de processament gràfic |
| Popis: | This article evaluates the current support for heterogeneous OpenMP 5.2 applications regarding the simultaneous activation of host and device computing units (e.g., CPUs, GPUs, or FPGAs). The article identifies limitations in the current OpenMP specification and describes the design and implementation of novel OpenMP extensions and runtime support for heterogeneous parallel programming. The Compute Unit (CUs) abstraction is introduced in the OpenMP programming model. The Compute Unit abstraction is defined in terms of an aggregation of computing elements (e.g., CPUs, GPUs, FPGAs). On top of CUs, the article describes dynamic work sharing constructs and schedulers that address the inherent differences in compute power of host and device CUs. New constructs and the corresponding runtime support are described for the new abstractions. The article evaluates the case of a hybrid multilevel parallelization of the NPB-MZ benchmark suite. The implementation exploits both coarse-grain and fine-grain parallelism, mapped to CUs of different nature (GPUs and CPUs). All CUs are activated using the new extensions and runtime support. We compare hybrid and nonhybrid executions under two state-of-the-art work-distribution schemes (Static and Dynamic Task schedulers). On a computing node composed of one AMD EPYC 7742 @ 2.250GHz (64 cores and 2 threads/core, totalling 128 threads per node) and 2 GPU AMD Radeon Instinct MI50 with 32GB, hybrid executions present speedups from 1.08 up to 3.18 with respect to a nonhybrid GPU implementation, depending on the number of activated CUs. ; This work was supported by the Spanish Ministry of Science and Technology (PID2019-107255GB). ; Peer Reviewed ; Postprint (published version) |
| Druh dokumentu: | article in journal/newspaper |
| Popis súboru: | 22 p.; application/pdf |
| Jazyk: | English |
| Relation: | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107255GB-C22/ES/UPC-COMPUTACION DE ALTAS PRESTACIONES VIII/; Gonzalez, M.; Morancho, E. Compute units in OpenMP: extensions for heterogeneous parallel programming. "Concurrency and computation: practice and experience", 10 Gener 2024, vol. 36, núm. 1, article e7885.; http://hdl.handle.net/2117/394656 |
| DOI: | 10.1002/cpe.7885 |
| Dostupnosť: | http://hdl.handle.net/2117/394656 https://doi.org/10.1002/cpe.7885 |
| Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International ; http://creativecommons.org/licenses/by-nc-nd/4.0/ ; Open Access |
| Prístupové číslo: | edsbas.C63D29AA |
| Databáza: | BASE |
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