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Study on Parallel Algorithm for Solving Large Matrix Eigenproblem

Tao Zhao, Xuebin Chi, Zhonghua Lu, Yonghua Zhao

Open publisher page 4 citations

Abstract

Based on the parallel algorithm for restarted Arnoldi method by using data parallel model, a parallel algorithm for refined restarted Arnoldi method is presented. To impair the negative impact on parallel performance due to weak scalability, the parallel algorithm presented implements parallel computing refined vectors by using task graph model and reduces the communication cost. As a result, the algorithm achieves parallel computing efficiently. Numerical experiments on KD-50-I show that the parallel algorithm presented performs good scalability and efficiency.

About this research paper

What this paper is about

Based on the parallel algorithm for restarted Arnoldi method by using data parallel model, a parallel algorithm for refined restarted Arnoldi method is presented. To impair the negative impact on parallel performance due to weak scalability, the parallel algorithm presented implements parallel computing refined vectors by using task graph model and reduces the communication cost. As a result, the algorithm achieves parallel computing efficiently. Numerical experiments on KD-50-I show that the parallel algorithm presented performs good scalability and efficiency.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Method / approach

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Available abstract

Based on the parallel algorithm for restarted Arnoldi method by using data parallel model, a parallel algorithm for refined restarted Arnoldi method is presented. To impair the negative impact on parallel performance due to weak scalability, the parallel algorithm presented implements parallel computing refined vectors by using task graph model and reduces the communication cost. As a result, the algorithm achieves parallel computing efficiently. Numerical experiments on KD-50-I show that the parallel algorithm presented performs good scalability and efficiency.

Key concepts: Computer science, Parallel algorithm, Scalability, Parallel computing, Cost efficiency, Algorithm, Parallel processing, Task (project management)

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