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Graphics processing unit based acceleration of electromagnetic transients simulation

机译:基于图形处理单元的电磁瞬变仿真的加速度

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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.
机译:本文介绍了采用基于GPU的计算来加速EMT模拟的新颖的并行化方法。本文在该地区之前发布的作品早期延伸,通过利用额外的并行性来加速EMT模拟。使用2D平行矩阵 - 向量乘法,其比以前的1D方法更快。此外,本文实现了更简单的GPU特定的稀疏技术,以进一步加快模拟,因为可用的CPU基稀疏技术不适合GPU。此外,作为先前作品的扩展,本文展示了电力电子子系统的建模。考虑一个低粒度系统,即,具有大量连接到具有少数传输线的其他总线的一个具有少量传输线的大型总线的一个。也是一个高粒度,其中小集群连接到其他簇,从而需要更多互连的传输线。将基于GPU的计算的计算时间与CPU上的顺序实现的计算时间进行了比较。本文展示了与CPU仿真相比,GPU仿真的两个令人惊讶的差异。首先,包含稀疏性仅在基于GPU的模拟时间内进行轻微减少。其次过度粒度,即使它似乎增加了并行可计算子系统的数量,显着减慢了基于GPU的模拟。

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