Compiling MATLAB programs to ScaLAPACK: exploiting task and data parallelism

We suggest a new approach aimed at reducing the effort required to program distributed-memory multicomputers. The key idea in our approach is to automatically convert a program written in a library-based programming language (MATLAB) to a parallel program based on the ScaLAPACK parallel library. In the process of performing this conversion, we apply compiler optimizations that simultaneously exploit task and data parallelism. As our results show, our approach is feasible and practical and our optimization provides significant performance benefits.