A performance- and energy-oriented extended tuning process for time-step-based scientific applications

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00005336
URN to cite this document: urn:nbn:de:bvb:703-epub-5336-3

Title data

Kalinnik, Natalia ; Kiesel, Robert ; Rauber, Thomas ; Richter, Marcel ; Rünger, Gudula:
A performance- and energy-oriented extended tuning process for time-step-based scientific applications.
In: The Journal of Supercomputing. Vol. 76 (2021) . - pp. 3484-3515.
ISSN 1573-0484
DOI der Verlagsversion: https://doi.org/10.1007/s11227-020-03402-y

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Abstract

Scientific application codes are often long-running time- and energy-consuming parallel codes, and the tuning of these methods towards the characteristics of a specific hardware is essential for a good performance. However, since scientific software is often developed over many years, the application software usually survives several hardware generations, which might make a re-tuning of the existing codes necessary. To simplify the tuning process, it would be beneficial to have software with inherent tuning possibilities. In this article, we explore the possibilities of tuning methods for time-step-based applications. Two different time-step-based application classes are considered, which are solution methods for ordinary differential equations and particle simulation methods. The investigation comprises a broad range of tuning possibilities, starting from the choice of algorithms, the parallel programming model, static implementation variants, input characteristics as well as hardware parameters for parallel execution. An experimental investigation shows the different characteristics of the application classes on different multicore systems. The results show that a combination of offline and online tuning leads to good tuning results. However, due to the different input characteristics of the two application classes, regular versus irregular, different tuning aspects are most essential.

Further data

Item Type:	Article in a journal
Keywords:	time-stepping methods; ordinary differential equation; particle simulation; offline tuning; online tuning; multicore
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science
Institutions of the University:	Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science II > Chair Applied Computer Science II - Univ.-Prof. Dr. Thomas Rauber Faculties Faculties > Faculty of Mathematics, Physics und Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science II
Language:	English
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-5336-3
Date Deposited:	17 Mar 2021 11:22
Last Modified:	17 Mar 2021 11:22
URI:	https://epub.uni-bayreuth.de/id/eprint/5336

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