Data - Flow Framework for

This paper presents a framework, based on global array data-ow analysis, to reduce communication costs in a program being compiled for a distributed memory machine. This framework applies techniques for partial redundancy elimination to available section descriptors, a novel representation of communication involving array sections. With a single framework, we are able to capture numerous optimizations like (i) vectorizing communication, (ii) eliminating communication that is redundant on any control ow path, (iii) reducing the amount of data being communicated, (iv) reducing the number of processors to which data must be communicated, and (v) moving communication earlier to hide latency, and to subsume previous communication. Further, the explicit representation of availability of data in our framework allows processors other than the owners also to send values needed by other processors, leading to additional opportunities for optimizing communication. Another contribution of this paper is to show that the bidirectional problem of eliminating partial redundancies can be decomposed into simpler uni-directional problems, in the context of communication as well.