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Graphics-processing-unit-based acceleration of electromagnetic transients simulation.

Debnath, Jayanta K.; Gole, Aniruddha M.; Fung, Wai-Keung


Jayanta K. Debnath

Aniruddha M. Gole

Wai-Keung Fung


This paper presents a novel parallelization approach to speedup EMT simulation, using GPU-based computing. This paper extends earlier published works in the area, by exploiting additional parallelism to accelerate EMT simulation. A 2D-parallel matrix-vector multiplication is used that is faster than previous 1D-methods. Also this paper implements a simpler GPU-specific sparsity technique to further speed up the simulations as available CPU-based sparse techniques are not suitable for GPUs. Additionally, as an extension to previous works, this paper demonstrates modelling of a power electronic subsystem. A low granularity system, i.e. one with a large cluster of busses connected to others with a few transmission lines is considered, as is also a high granularity where a small cluster of busses is connected to other clusters thereby requiring more interconnecting transmission lines. Computation times for GPU-based computing are compared with the computation times for sequential implementations on the CPU. The paper shows two surprising differences of GPU simulation in comparison with CPU simulation. Firstly, the inclusion of sparsity only makes minor reductions in the GPU-based simulation time. Secondly excessive granularity, even though it appears to increase the number of parallel computable subsystems, significantly slows down the GPU-based simulation.

Journal Article Type Article
Publication Date Oct 1, 2016
Journal IEEE transactions on power delivery
Print ISSN 0885-8977
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 31
Issue 5
Pages 2036-2044
Institution Citation DEBNATH, J.K., GOLE, A.M. and FUNG, W.-K. 2016. Graphics-processing-unit-based acceleration of electromagnetic transients simulation. IEEE transactions on power delivery [online], 31(5), pages 2036-2044. Available from:
Keywords EMT simulation; Power systems simulation; Power system modelling; GPU computing; CUDAC programming; Parallel algorithms


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