Parallel implementation of the BiCGStab(2) method in GPU using CUDA and matlab for solution of linear systems
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2014
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Resumo
This paper presents a parallel implementation of the hybrid BiCGStab(2) (bi-conjugate gradient stabilized) iterative method in a GPU (graphics processing unit) for solution of large and sparse linear systems. This implementation uses the CUDA-Matlab integration, in which the method operations are performed in a GPU core using Matlab built-in functions. The goal is to show that the exploitation of parallelism by using this new technology can provide a significant computational performance. For the validation of the work, we compared the proposed implementation with a BiCGStab(2) sequential and parallelized implementation in the C and CUDA-C languages. The results showed that the proposed implementation is more efficient and can be viable for simulations being carried out with quality and in a timely manner. The gains in computational efficiency were 76x and 6x compared to the implementation in C and CUDA-C, respectively.
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Matlab, GPU, CUDA, BiCGStab(2)
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PAULA, Lauro Cássio Martins de; SOARES, Anderson da Silva. Parallel implementation of the BiCGStab(2) method in GPU using CUDA and matlab for solution of linear systems. Journal of Communication and Computer, New York, v. 11, n. 4, p. 339-346, 2014.