Minimizing data and synchronization costs in one-way communication

Minimizing communication and synchronization costs is crucial to the realiz ation of the performance potential of parallel computers. This paper presen ts a general technique which uses a global data-flow framework to optimize communication and synchronization in the context of the one-way communicati on model. In contrast to the conventional send/receive message-passing comm unication model, one-way communication is a new paradigm that decouples mes sage transmission and synchronization. In parallel machines with appropriat e low-level support, this may open up new opportunities not only to further optimize communication. but also to reduce the synchronization overhead. W e present optimization techniques using our framework for eliminating redun dant data communication and synchronization operations. Our approach works with the most general data alignments and distributions in languages like H igh Performance Fortran (HPF) and uses a combination of the traditional dat a-flow analysis and polyhedral algebra. Empirical results for several scien tific benchmarks on a Gray T3E multiprocessor machine demonstrate that our approach is successful in reducing the number of data (communication) and s ynchronization messages, thereby reducing the overall execution times.