Exploring Self-Adaptivity Towards Performance and Energy for Time-Stepping Methods
| Autor: | Robert Kiesel, Gudula Rünger, Thomas Hauber, Natalia Kalinnik, Marcel Richter |
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| Rok vydání: | 2018 |
| Předmět: |
020203 distributed computing
Computer science Differential equation 010103 numerical & computational mathematics 02 engineering and technology Function (mathematics) Energy consumption Self adaptivity 01 natural sciences Measure (mathematics) Time stepping Computer engineering 0202 electrical engineering electronic engineering information engineering 0101 mathematics Energy (signal processing) Sparse matrix computations |
| Zdroj: | SBAC-PAD |
| DOI: | 10.1109/cahpc.2018.8645887 |
| Popis: | Time-stepping simulation methods offer potential for self-adaptivity, since the first time steps of the simulation can be used to explore the hardware characteristics and measure which of several available implementation variants leads to a good performance and energy consumption on the given hardware platform. The version with the best performance or the smallest energy consumption can then be used for the remaining time steps. However, the number of variants to test may be quite large and different simulation methods may require different approaches for self-adaptivity. In this article, we explore the potential for self-adaptivity of several methods from scientific computing. In particular, we consider particle simulation methods, solution methods for differential equations, as well as sparse matrix computations and explore the potential for self-adaptivity of these methods, considering both performance and energy consumption as target function. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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