Buffer-Safe and Cost-Driven Communication Optimization

This paper presents a new approach for optimizing communication of data parallel programs. Our techniques are based on unidirectional bit-vector data flow analyses that enable vectorizing, coalescing and aggregating communication, and overlapping communication with computation both within and across loop nests. Previous techniques are based on fixed communication optimization strategies whose quality is very sensitive to changes of machine and problem sizes. Our algorithm is novel in that we carefully examine tradeoffs between enhancing communication latency hiding and reducing the number and volume of messages by systematically evaluating a reasonable set of promising communication placements for a given program covering several (possibly conflicting) communication guiding profit motives. We useP3T, a state-of-the-art performance estimator, to ensure communication buffer safety and to find the best communication placement of all created ones. First results show that our method implies a significant reduction in communication costs and demonstrate the effectiveness of this analysis in improving the performance of programs.