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Jan Himmelspach, Roland Ewald, Stefan Leye, and Adelinde M Uhrmacher (2010)

Enhancing the Scalability of Simulations by Embracing Multiple Levels of Parallelization

In: Proceedings of the 2010 International Workshop on High Performance Computational Systems Biology, pp. 57-66, IEEE CPS.

Current and upcoming architectures of desktop and high performance computers offer increasing means for parallel execution. Since the computational demands induced by ever more realistic models increase steadily, this trend is of growing importance for systems biology. Simulations of these models may involve the consideration of multiple parameter combinations, their replications, data collection, and data analysis—all of which offer different opportunities for parallelization. We present a brief theoretical analysis of these opportunities in order to show their potential impact on the overall computation time. The benefits of using more than one opportunity for parallelization are illustrated by a set of benchmark experiments, which furthermore show that parallelizability should be exploited in a flexible manner to achieve speedup.

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