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Testing Tesla architecture for scientific computing: The performance of matrix-vector product

机译:测试Tesla架构进行科学计算:矩阵矢量产品的性能

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The paper presents results of several experiments evaluating the performance of NVIDIA processors, implementing a new Tesla architecture, in matrix-vector multiplication. Three matrix forms, dense, banded and sparse, are considered together with three hardware platforms: NVIDIA Tesla C870 computing board, NVIDIA GeForce 8800 GTX graphics card and one of the newest Intel Xeon processors, E5462, with 1.6 GHz front side bus speed. The conclusions from experiments indicate what speed-ups can be expected when, instead of standard CPUs, accelerators in the form of presented GPUs are used for considered computational kernels.
机译:本文介绍了在矩阵矢量乘法中评估NVIDIA处理器的性能评估NVIDIA处理器的性能的结果。三个矩阵形式,密集,带状和稀疏,与三个硬件平台一起考虑:NVIDIA Tesla C870计算板,NVIDIA GeForce 8800 GTX显卡和最新的英特尔Xeon处理器E5462,具有1.6 GHz前侧总线速度。来自实验的结论表明,当呈现的GPU的形式的速度而不是标准CPU时,可以预期速度可以预期的速度,用于考虑计算内核。

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