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

机译:测试Tesla架构以进行科学计算:矩阵向量乘积的性能

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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:本文介绍了一些实验的结果,这些实验评估了NVIDIA处理器的性能,并在矩阵矢量乘法中实现了新的Tesla架构。考虑了三种矩阵形式(密集,带状和稀疏)以及三个硬件平台:NVIDIA Tesla C870计算板,NVIDIA GeForce 8800 GTX图形卡和最新的Intel Xeon处理器之一E5462,具有1.6 GHz的前端总线速度。实验得出的结论表明,当使用代替所显示的GPU形式的加速器代替标准CPU来考虑计算内核时,可以期望达到何种速度提升。

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