A Compressed Diagonals Remapping Technique for Dynamic Data Redistribution on Banded Sparse Matrix
The Journal of Supercomputing
A compressed diagonals remapping technique for dynamic data redistribution on banded sparse matrix
ISPA'03 Proceedings of the 2003 international conference on Parallel and distributed processing and applications
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In many scientific applications, dynamic data redistribution of sparse matrix is used to enhance the performance of SPMD programs. Since the redistribution is performed at runtime, it is critical to the performance of a parallel program. In this paper, we present a new method, which aims to the efficiency of block-cyclic data redistribution of sparse matrix. The main idea of the proposed technique is first to develop closed forms for generating the vector index set of each source/destination processor. Based on the vector index set and the non-zero structure of sparse matrix, two efficient algorithms, vector2message (v2m) and message2vector (m2v) can be derived. The v2m algorithm is used to extract non-zero elements from source matrix and packs them into messages while m2v is used to unpack messages and construct the destination matrix. A theoretical model to analyze the performance of the proposed technique is also presented in this paper. Our method is compared to a dense redistribution strategy and the Histogram method on an IBM SP2 parallel machine. The experimental results show that our techniques can efficiently perform sparse matrix data redistribution.