Abstract
Scientific applications do frequently suffer from limited compute performance. In this article, we investigate the suitability of specialized computer chips to overcome this limitation. An enhanced Poisson Boltzmann program is ported to the graphics processing unit and the application specific integrated circuit MDGRAPE-3 and resulting execution times are compared to the conventional performance obtained on a modern central processing unit. Speed Up factors are measured and an analysis of numerical accuracy is provided. On both specialized architectures the improvement is increasing with problem size and reaches up to a Speed Up factor of 39 x for the largest problem studied. This type of alternative high performance computing can significantly improve the performance of demanding scientific applications.
Original language | English |
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Pages (from-to) | 2351-2357 |
Number of pages | 7 |
Journal | Journal of Computational Chemistry |
Volume | 30 |
Issue number | 14 |
DOIs | |
Publication status | Published - 2009 Nov 15 |
Keywords
- ASIC
- GPU
- Implicit solvation models
- MDGRAPE-3
- Poisson boltzmann
- Solvation
ASJC Scopus subject areas
- Chemistry(all)
- Computational Mathematics