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	Improving performance of matrix multiplication and FFT on GPU
	Cui, Xiang ; Chen, Yifeng ; Mei, Hong
	2009
英文摘要	In this paper we discuss about our experiences in improving the performance of two key algorithms: the single-precision matrix-matrix multiplication subprogram (SGEMM of BLAS) and single-precision FFT using CUDA. The former is computation-intensive, while the latter is memory bandwidth or communication-intensive. A peak performance of 393 Gflops is achieved on NVIDIA GeForce GTX280 for the former1, about 5% faster than the CUBLAS 2.0 library. Better FFT performance results are obtained for a range of dimensions. Some common principles are discussed for the design and implementation of many-core algorithms. ? 2009 IEEE.; EI; 0
语种	英语
DOI标识	10.1109/ICPADS.2009.8
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/153569]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Cui, Xiang,Chen, Yifeng,Mei, Hong. Improving performance of matrix multiplication and FFT on GPU. 2009-01-01.

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