LinSolv: a Case Study in Strategic Parallelism

This paper discusses the parallelisation and performance tuning of a typical computer algebra algorithm, LinSolv, using evaluation strategies. We present three steps in the parallelisation process starting with a naive parallel version. As this algorithm uses innnite data structures as intermediate values it is necessary to deene very sophisticated strategies in order to improve parallel performance. We also compare the strategic parallel code with pre-strategy code. This comparison shows how evaluation strategies help to localise changes needed for parallelisation. In particular, the separation between algorithmic and parallel code makes the structure of the parallelism much clearer.