Exascale machines require new programming paradigms and runtimes
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| Titel: | Exascale machines require new programming paradigms and runtimes |
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| Autoren: | da Costa, Georges, Fahringer, Thomas, Rico-Gallego, Juan-Antonio, Grasso, Ivan, Hristov, Atanas, Karatza, Helen D., Lastovetsky, Alexey, Marozzo, Fabrizio, Petcu, Dana, Stavrinides, Georgios L., Talia, Domenico, Trufio, Paolo, Astsatryan, Hrachya |
| Weitere Verfasser: | Système d’exploitation, systèmes répartis, de l’intergiciel à l’architecture (IRIT-SEPIA), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Universität Innsbruck Innsbruck = University of Innsbruck, Universidad de Extremadura - University of Extremadura (UEX), Aristotle University of Thessaloniki, University College Dublin Dublin (UCD), Università della Calabria Arcavacata di Rende, Italia = University of Calabria Italy = Université de Calabre Italie (UniCal), Universitatea de Vest din Timișoara România = West University of Timișoara Romania = Université Ouest de Timișoara Roumanie (UVT), National Academy of Sciences of the Republic of Armenia Yerevan (NAS RA) |
| Quelle: | ISSN: 2409-6008 ; EISSN: 2313-8734 ; Supercomputing Frontiers and Innovations. |
| Verlagsinformationen: | CCSD South Ural State University |
| Publikationsjahr: | 2015 |
| Bestand: | Université Toulouse III - Paul Sabatier: HAL-UPS |
| Schlagwörter: | Parallel computing systems, [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI], [INFO.INFO-AR]Computer Science [cs]/Hardware Architecture [cs.AR], [INFO.INFO-ES]Computer Science [cs]/Embedded Systems, [INFO.INFO-OS]Computer Science [cs]/Operating Systems [cs.OS] |
| Beschreibung: | International audience ; Extreme scale parallel computing systems will have tens of thousands of optionally accelerator-equiped nodes with hundreds of cores each, as well as deep memory hierarchies and complex interconnect topologies. Such Exascale systems will provide hardware parallelism at multiple levels and will be energy constrained. Their extreme scale and the rapidly deteriorating reliablity of their hardware components means that Exascale systems will exhibit low mean-time-between-failure values. Furthermore, existing programming models already require heroic programming and optimisation efforts to achieve high efficiency on current supercomputers. Invariably, these efforts are platform-specific and non-portable. In this paper we will explore the shortcomings of existing programming models and runtime systems for large scale computing systems. We then propose and discuss important features of programming paradigms and runtime system to deal with large scale computing systems with a special focus on data-intensive applications and resilience. Finally, we also discuss code sustainability issues and propose several software metrics that are of paramount importance for code development for large scale computing systems. |
| Publikationsart: | article in journal/newspaper |
| Sprache: | English |
| DOI: | 10.14529/jsfi150201 |
| Verfügbarkeit: | https://hal.science/hal-03517065 https://hal.science/hal-03517065v1/document https://hal.science/hal-03517065v1/file/dacosta_16839.pdf https://doi.org/10.14529/jsfi150201 |
| Rights: | info:eu-repo/semantics/OpenAccess |
| Dokumentencode: | edsbas.1BBEDE8F |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | International audience ; Extreme scale parallel computing systems will have tens of thousands of optionally accelerator-equiped nodes with hundreds of cores each, as well as deep memory hierarchies and complex interconnect topologies. Such Exascale systems will provide hardware parallelism at multiple levels and will be energy constrained. Their extreme scale and the rapidly deteriorating reliablity of their hardware components means that Exascale systems will exhibit low mean-time-between-failure values. Furthermore, existing programming models already require heroic programming and optimisation efforts to achieve high efficiency on current supercomputers. Invariably, these efforts are platform-specific and non-portable. In this paper we will explore the shortcomings of existing programming models and runtime systems for large scale computing systems. We then propose and discuss important features of programming paradigms and runtime system to deal with large scale computing systems with a special focus on data-intensive applications and resilience. Finally, we also discuss code sustainability issues and propose several software metrics that are of paramount importance for code development for large scale computing systems. |
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| DOI: | 10.14529/jsfi150201 |