Optimizing irregular computations on SIMD machines: a case study

Data-parallel computations with regular structure fixed data size and predictable control patterns can be implemented efficiently on SIMD architectures. However many large applications have irregular structure, either data sets that vary in size as the computation progresses or control structures that select different subsets of the processors at each stage of the computation. In this paper we describe a stochastic biology simulation and some of the methods we used to improve its performance on the MasPar MP-1104. We present a simple model for evaluating the performance of a data parallel application and use the model to improve the performance of the simulator