Abstract
The parallel solution of multiple systems of initial-value problems (IVPs) in ordinary differential equations is challenging because the amount of computation involved in solving a given IVP is generally not well correlated with that of solving another. In this paper, we describe how to efficiently solve multiple systems of stiff IVPs in parallel within a single-instruction, multiple-data (SIMD) implementation on the Cell Broadband Engine (CBE) of the RODAS solver for stiff IVPs. We solve two systems of stiff IVPs simultaneously on each of the eight synergistic processing elements per CBE chip for a total of 16 systems of IVPs. We demonstrate a speedup of 1.89 (a parallel efficiency of over 94%) over the corresponding serial code on a realistic example involving the operation of a chemical reactor. The techniques described apply to other multi-core processors besides the CBE and can be expected to increase in importance as computer architectures evolve to feature larger word sizes.
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