Abstract
The bottleneck of most data analyzing systems, signal processing systems, and intensive computing systems is matrix decomposition. The Cholesky factorization of a sparse matrix is an important operation in numerical algorithms field. This paper presents a Multi-phased Parallel Cholesky Factorization (MPCF) algorithm, and then gives the implementation on a multi-core machine. A performance result shows that the system can reach 85.7 Gflop/s on a single PowerXCell processor and bulk of computation can reach to 94% of peak performance. © 2010 Springer-Verlag.
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CITATION STYLE
Wang, B., Ge, N., Peng, H., Wei, Q., Li, G., & Gong, Z. (2010). Design and implementation of parallelized cholesky factorization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5938 LNCS, pp. 390–397). https://doi.org/10.1007/978-3-642-11842-5_54
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