Applying StarPU runtime system to scientific applications: Experiences and lessons learned
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| Názov: | Applying StarPU runtime system to scientific applications: Experiences and lessons learned |
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| Autori: | Tzanos, Georgios, Soni, Vineet, Prouveur, Charles, Haefele, Matthieu, Zouzoula, Stavroula, Papadopoulos, Lazaros, Thibault, Samuel, Vandenbergen, Nicolas, Pleiter, Dirk, Soudris, Dimitrios |
| Prispievatelia: | National Technical University of Athens (NTUA), Maison de la Simulation (MDLS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de Recherche en Informatique et en Automatique (Inria)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour (LIUPPA), Université de Pau et des Pays de l'Adour (UPPA), Linköpings Universitet = Linköping University, STatic Optimizations, Runtime Methods (STORM), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de l'Université de Bordeaux, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Forschungszentrum Jülich GmbH, Helmholtz-Gemeinschaft = Helmholtz Association, European Project: 801015,H2020-FETHPC-2016-2017,H2020-FETHPC-2017,EXA2PRO(2018) |
| Zdroj: | POMCO 2020 - 2nd International Workshop on Parallel Optimization using/for Multi- and Many-core High Performance Computing ; https://inria.hal.science/hal-02985721 ; POMCO 2020 - 2nd International Workshop on Parallel Optimization using/for Multi- and Many-core High Performance Computing, Dec 2020, Barcelona / Virtual, Spain |
| Informácie o vydavateľovi: | CCSD |
| Rok vydania: | 2020 |
| Zbierka: | HAL e2s UPPA (Université de Pau et des Pays de l'Adour) |
| Predmety: | HPC, task-based programming models, StarPU, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC] |
| Geografické téma: | Spain |
| Time: | Barcelona / Virtual, Spain |
| Popis: | International audience ; Task-based runtime systems are adopted by application developers for their valuable features including flexibility of execution and optimized resource management. However, the use of such advanced programming models in complex HPC applications often requires significant training time and programming effort. In this work, we share experiences and lessons learned from the use of StarPU in three independent projects of various complexity. We reach conclusions, with respect to training, programming effort, and existing challenges, that are useful to the communities of application developers, as well as to the developers of runtime systems. Finally, we suggest extensions to the runtime systems beneficial to application developers. |
| Druh dokumentu: | conference object |
| Jazyk: | English |
| Relation: | info:eu-repo/grantAgreement//801015/EU/Enhancing Programmability and boosting Performance Portability for Exascale Computing Systems/EXA2PRO |
| Dostupnosť: | https://inria.hal.science/hal-02985721 https://inria.hal.science/hal-02985721v1/document https://inria.hal.science/hal-02985721v1/file/POMCO2020-camera-ready.pdf |
| Rights: | https://about.hal.science/hal-authorisation-v1/ ; info:eu-repo/semantics/OpenAccess |
| Prístupové číslo: | edsbas.8199C638 |
| Databáza: | BASE |
Nájsť tento článok vo Web of Science | Abstrakt: | International audience ; Task-based runtime systems are adopted by application developers for their valuable features including flexibility of execution and optimized resource management. However, the use of such advanced programming models in complex HPC applications often requires significant training time and programming effort. In this work, we share experiences and lessons learned from the use of StarPU in three independent projects of various complexity. We reach conclusions, with respect to training, programming effort, and existing challenges, that are useful to the communities of application developers, as well as to the developers of runtime systems. Finally, we suggest extensions to the runtime systems beneficial to application developers. |
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