Issue No.12 - December (1999 vol.10)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/71.819945
<p><b>Abstract</b>—Run-time array redistribution is necessary to enhance the performance of parallel programs on distributed memory supercomputers. In this paper, we present an efficient algorithm for array redistribution from <it>cyclic(x)</it> on <tmath>$P$</tmath> processors to <it>cyclic(Kx)</it> on <tmath>$Q$</tmath> processors. The algorithm reduces the overall time for communication by considering the data transfer, communication schedule, and index computation costs. The proposed algorithm is based on a generalized circulant matrix formalism. Our algorithm generates a schedule that minimizes the number of communication steps and eliminates node contention in each communication step. The network bandwidth is fully utilized by ensuring that equal-sized messages are transferred in each communication step. Furthermore, the time to compute the schedule and the index sets is significantly smaller. It takes <tmath>$O(max(P,Q))$</tmath> time and is less than 1 percent of the data transfer time. In comparison, the schedule computation time using the state-of-the-art scheme (which is based on the bipartite matching scheme) is 10 to 50 percent of the data transfer time for similar problem sizes. Therefore, our proposed algorithm is suitable for run-time array redistribution. To evaluate the performance of our scheme, we have implemented the algorithm using C and MPI on an IBM SP2. Results show that our algorithm performs better than the previous algorithms with respect to the total redistribution time, which includes the time for data transfer, schedule, and index computation.</p>
Block-cyclic distribution, redistribution algorithms, interprocessor communication.
Neungsoo Park, Viktor K. Prasanna, Cauligi S. Raghavendra, "Efficient Algorithms for Block-Cyclic Array Redistribution Between Processor Sets", IEEE Transactions on Parallel & Distributed Systems, vol.10, no. 12, pp. 1217-1240, December 1999, doi:10.1109/71.819945