A communication placement framework with unified dependence and data-flow analysis

Communication placement analysis is an important step in the compilation of data-parallel programs for multiproces-sor systems. This paper presents a communication placement framework that minimizes frequency of communication , eliminates redundant communication, and maximizes communication latency hiding. The paper shows how data-dependence information can be combined with data-ow analysis to devise simpler and cleaner data-ow problems. It shows how to develop equations for balanced communication placement using a set of uni-directional analyses { with an independent equation system for each placement criterion. This structure allows the framework to support vector message pipelining { an important optimization for programs with loop-carried dependences { but, that was not supported by any previous data-ow framework. The paper also describes how other optimizations, such as partially redundant communication elimination and message coalesc-ing, are supported by the framework. Finally, the paper presents experimental results to prove the eecacy of our placement analysis.