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A Parameter Selection Process by Data Analysis for Tuning Multi-threaded Time-Stepping Algorithms

Title data

Rauber, Thomas ; Rünger, Gudula:
A Parameter Selection Process by Data Analysis for Tuning Multi-threaded Time-Stepping Algorithms.
In: 2020 Seventh International Conference on Software Defined Systems (SDS). - Piscataway, NJ : IEEE , 2020 . - pp. 43-50
ISBN 978-1-7281-7219-4
DOI: https://doi.org/10.1109/SDS49854.2020.9143911

Abstract in another language

Many applications from science and engineering can be simulated by time-stepping algorithms. Due to a possibly large number of simulation time steps and an expensive loop body in each time step, the execution of such algorithms can be quite time consuming and may also require a high amount of energy and power for the computation. Execution time, energy, and power can vary for varying application specific and architecture specific parameters. Also, the lowest execution time does not necessarily leads to a low power consumption or energy consumption. In this article, we are concerned with the selection of specific parameter values which lead to a low time and/or energy and/or power consumption. Specifically, we propose an energy-aware parameter selection process that is the basis for a software-defined support of an energy and power efficient execution. The process includes a data gathering phase, a parameter selection phase based on the data sets and a parameter adaption phase at run-time combining data tabulation and data monitoring. A multi-threaded scientific algorithm solving a partial differential equation is chosen as an illustrating example.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: energy consumption; time-stepping scientific applications; energy-aware parameter selection
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
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 23 Oct 2020 10:31
Last Modified: 23 Oct 2020 10:31
URI: https://eref.uni-bayreuth.de/id/eprint/58608