Abstract
Multiphysics systems are used to simulate various physics phenomena given by Partial Differential Equations (PDEs). The most popular method of solving PDEs is Finite Element method. The simulations require large amount of computational power, that is mostly caused by extensive processing of matrices. The high computational requirements have led recently to parallelization of algorithms and to utilization of Graphic Processing Units (GPUs). To take advantage of GPUs, one of GPU programming models has to be used. In this paper, CUDA model developed by nVidia is used to implement two parallel matrix multiplication algorithms. To evaluate the effectiveness of these algorithms, several experiments have been performed. Results have been compared with results obtained by classic Central Processing Unit (CPU) matrix multiplication algorithm. The comparison shows that matrix multiplication on GPU significantly outperforms classic CPU approach.
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Krol, D., Zydek, D., Selvaraj, H. (2014). Matrix Multiplication in Multiphysics Systems Using CUDA. In: Swiątek, J., Grzech, A., Swiątek, P., Tomczak, J. (eds) Advances in Systems Science. Advances in Intelligent Systems and Computing, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-01857-7_48
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DOI: https://doi.org/10.1007/978-3-319-01857-7_48
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01856-0
Online ISBN: 978-3-319-01857-7
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