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Performance of one-level recursion parallel Strassen's algorithm on dual core processor

机译:单级递归并行Strassen算法在双核处理器上的性能

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Matrix multiplication is presumably one of the most important techniques in many scientific applications. Efficient implementation of this technique on the ubiquitous multi-cores is therefore critical to the performance of this broad range of applications. The execution time of sequential and parallel implementation of the algorithms were measured, analyzed and interpreted. The main aim of this research work is to compare the speedup obtainable from executing one-level recursion parallel Strassen's matrix multiplication algorithm on multi-core processors. The programs were written in C++/OpenMP. The result of the research work showed significant performance of the parallel programs of the Strassen's algorithm for large matrix size. It was also observed that Strassen's algorithm performs better for large matrix size while having the same performance as the Traditional algorithm for small matrices. The result suggested that with one step recursion, for both small and large matrix sizes Strassen's algorithm is the best choice.
机译:矩阵乘法可能是许多科学应用中最重要的技术之一。因此,在普遍存在的多核上有效实施此技术对于广泛应用的性能至关重要。测量,分析和解释了算法的顺序和并行执行的执行时间。这项研究工作的主要目的是比较在多核处理器上执行一级递归并行Strassen矩阵乘法的速度。这些程序是用C ++ / OpenMP编写的。研究工作的结果表明,对于大型矩阵,Strassen算法的并行程序具有显着的性能。还观察到Strassen算法对于较大的矩阵大小表现更好,同时具有与传统的针对小矩阵的算法相同的性能。结果表明,通过一步递归,对于大小矩阵都可以使用Strassen算法。

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