A Framework for Efficient Data Redistribution on Distributed Memory Multicomputers

Array redistribution is required often in programs on distributed memory parallel computers. It is essential to use efficient algorithms for redistribution; otherwise the performance of the programs will degrade considerably. The redistribution overheads consist of two parts: index computation and inter-processor communication. In this paper, by using a notation for the local data description called an LDD, we propose a framework to optimize the array redistribution algorithm both in index computation and inter-processor communication. That is, our work makes an effort to optimize not only the computation cost but also communication cost for array redistribution algorithms. We present an efficient index computation method and generate a schedule that minimizes the number of communication steps and eliminates node contention in each communication step. Some experiments show the efficiency and flexibility of our techniques.