Multiprocessor implementation of algorithms for ordinary differential equations

Multiprocessor computers constitute a cost-effective alternative to supercomputers for applications that require the solution of large sets of ordinary differential equations. The efficient use of multiprocessor comput ers however, requires tools for generation of parallel applications. This paper presents a general methodology for parallelization of the integration algorithms through a heuristic procedure for static multiprocessor scheduling of the computations involved. The procedure partitions, distributes and schedules the entire computation, based on decomposition of the mathematical models. Both problems are addressed: (i) minimize the completion time for a specified number of processors, and (ii) minimize the number of processors required to achieve a specified performance. The procedure combines high performance and simplicity for a wide variety of mathematical models, numerical algorithms and multiprocessor architec tures.