Run-Time Techniques for Parallelizing Sparse Matrix Problems

Sparse matrix problems are difficult to parallelize efficiently on message-passing machines, since they access data through multiple levels of indirection. Inspector/executor strategies, which are typically used to parallelize such problems impose significant preprocessing overheads. This paper describes the run-time support required by new compilation techniques for sparse matrices and evaluates their performance, highlighting optimizations and improvements over previous techniques.