摘要： 针对NVIDIA公司的CUDA技术用Geforce8800GT在Visual Studio2008环境下进行测试，从程序运行时间比较判断CUBLAS库、CUDA内核程序、CUDA驱动API、C循环程序与Intel MKL库以及FFTW库与CUFFT库运行响应的差异。测试结果表明，在大规模矩阵乘法和快速傅里叶变换的应用方面，相对于CPU，利用GPU运算性能可提高25倍以上。
关键词:
矩阵乘法,
快速傅里叶变换,
并行计算,
GPU通用计算
Abstract: This paper introduces the result of a test that evaluates the effectiveness of Compute Unified Device Architecture(CUDA) using NVDIA GeForce8800GT and the compiler Visual Studio 2008. It tests the speed of NVIDIA CUBLAS, CUDA kernel, common C program, Intel MKL BLAS, CUDA driver API program, FFTW and CUFFT Library in matrix-multiplication and Fast Fourier Transform(FFT). Test result of the large scale data shows that the computing ability of GPU is 25 times better than that of CPU.
Key words:
matrix-multiplication,
Fast Fourier Transform(FFT),
parallel computation,
GPGPU
中图分类号:
肖 江;胡柯良;邓元勇. 基于CUDA的矩阵乘法和FFT性能测试[J]. 计算机工程, 2009, 35(10): 7-10.
XIAO Jiang; HU Ke-liang; DENG Yuan-yong. Ability Test for Matrix-Multiplication and FFT Based on CUDA[J]. Computer Engineering, 2009, 35(10): 7-10.