Expressing Massively Parallel Algorithms for Irregular Data Expressing Massively Parallel Algorithms for Irregular Data

In this paper we present a data-parallel language called MPL, for which the basic data structure is the graph. The purpose of this language is to program numerical algorithms that use irregular data, and to allow them to execute on distributed memory MIMD machines. We deene the graph data structure and give some examples of how irregular data structures can be described from graphs with our approach. We describe also the mechanism to specify a distribution, and present the compiling process based on the SPMD approach. We illustrate these topics by using as an example a block-Cholesky factorization algorithm for sparse matrices.