Abstract
The paper presents a novel Parallel Crout Algorithm (PCA) based on multi-core computer with Threading Building Blocks (TBB). TBB offers a rich and complete approach to express parallelism in a C++ program. PCA is decomposed into three-tier: data decomposition parallelism, task processing parallelism and data composition parallelism and it can improve the efficiency of solving linear systems. Compared with Sequential Crout Algorithm (SCA), PCA has advantages of high efficiency, cross-platform and scalability. SCA and PCA, which is based on TBB, are implemented with C++. The validities of both methods are verified by different scale of matrix. In order to improve decomposition rate, the paper optimizes the parameters of PCA. Experiments show that, compared with SCA, PCA can reached a faster solution speed and a higher efficiency and it takes full advantage of Symmetrical Multi-Processing computer.
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