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Isoefficiency in Practice: Configuring and Understanding the Performance of Task-based Applications

Shudler, Sergei ; Calotoiu, Alexandru ; Hoefler, Torsten ; Wolf, Felix (2017)
Isoefficiency in Practice: Configuring and Understanding the Performance of Task-based Applications.
22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Austin, USA (04.-08.02.2017)
doi: 10.1145/3018743.3018770
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Task-based programming offers an elegant way to express units of computation and the dependencies among them, making it easier to distribute the computational load evenly across multiple cores. However, this separation of problem decomposition and parallelism requires a sufficiently large input problem to achieve satisfactory efficiency on a given number of cores. Unfortunately, finding a good match between input size and core count usually requires significant experimentation, which is expensive and sometimes even impractical. In this paper, we propose an automated empirical method for finding the isoefficiency function of a task-based program, binding efficiency, core count, and the input size in one analytical expression. This allows the latter two to be adjusted according to given (realistic) efficiency objectives. Moreover, we not only find (i) the actual isoefficiency function but also (ii) the function one would yield if the program execution was free of resource contention and (iii) an upper bound that could only be reached if the program was able to maintain its average parallelism throughout its execution. The difference between the three helps to explain low efficiency, and in particular, it helps to differentiate between resource contention and structural conflicts related to task dependencies or scheduling. The insights gained can be used to co-design programs and shared system resources.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2017
Autor(en): Shudler, Sergei ; Calotoiu, Alexandru ; Hoefler, Torsten ; Wolf, Felix
Art des Eintrags: Bibliographie
Titel: Isoefficiency in Practice: Configuring and Understanding the Performance of Task-based Applications
Sprache: Englisch
Publikationsjahr: 26 Januar 2017
Ort: New York
Verlag: ACM
Buchtitel: PPoPP'17: Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Veranstaltungstitel: 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Veranstaltungsort: Austin, USA
Veranstaltungsdatum: 04.-08.02.2017
DOI: 10.1145/3018743.3018770
Kurzbeschreibung (Abstract):

Task-based programming offers an elegant way to express units of computation and the dependencies among them, making it easier to distribute the computational load evenly across multiple cores. However, this separation of problem decomposition and parallelism requires a sufficiently large input problem to achieve satisfactory efficiency on a given number of cores. Unfortunately, finding a good match between input size and core count usually requires significant experimentation, which is expensive and sometimes even impractical. In this paper, we propose an automated empirical method for finding the isoefficiency function of a task-based program, binding efficiency, core count, and the input size in one analytical expression. This allows the latter two to be adjusted according to given (realistic) efficiency objectives. Moreover, we not only find (i) the actual isoefficiency function but also (ii) the function one would yield if the program execution was free of resource contention and (iii) an upper bound that could only be reached if the program was able to maintain its average parallelism throughout its execution. The difference between the three helps to explain low efficiency, and in particular, it helps to differentiate between resource contention and structural conflicts related to task dependencies or scheduling. The insights gained can be used to co-design programs and shared system resources.

Freie Schlagworte: BMBF|01IH13001, DFG|SPPEXA 1648, DoE|DE-SC0015524
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Parallele Programmierung
Zentrale Einrichtungen
Zentrale Einrichtungen > Hochschulrechenzentrum (HRZ)
Zentrale Einrichtungen > Hochschulrechenzentrum (HRZ) > Hochleistungsrechner
Hinterlegungsdatum: 20 Apr 2018 12:23
Letzte Änderung: 28 Mai 2024 13:46
PPN: 518695220
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