@inproceedings{5400bfb84f18432798e8ecdd49cdd7db,
title = "An improved sparse matrix-vector multiplication kernel for solving modified equation in large scale power flow calculation on CUDA",
abstract = "Sparse matrix-vector multiplication (SpMV) is the most important kernel in parallel iterative method for solving modified equation in large scale power system power flow calculation. In this paper, one improved compressed sparse row (ICSR) storage used to settle the problem of the global memory alignment in the vector kernel on Graphics processing Unit (GPU) is given. The experiments on matrices with different sizes demonstrate that the vector kernel with ICSR storage format could improve the performance by 5\%-30\% for SpMV comparing with vector kernel with CSR, especially for the large-scale unstructured sparse matrix-vector product, the effect is more obvious.",
keywords = "CUDA, Compressed sparse row (CSR) storage format, GPU, Parallel algorithm, Sparse matrix-vector multiplication, modified equation, power flow calculation",
author = "Mei Yang and Cheng Sun and Zhimin Li and Dayong Cao",
year = "2012",
doi = "10.1109/IPEMC.2012.6259153",
language = "英语",
isbn = "9781457720864",
series = "Conference Proceedings - 2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012",
pages = "2028--2031",
booktitle = "Conference Proceedings - 2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012",
note = "2012 IEEE 7th International Power Electronics and Motion Control Conference - ECCE Asia, IPEMC 2012 ; Conference date: 02-06-2012 Through 05-06-2012",
}