Brook for GPUs: stream computing on graphics hardware
Brook for GPUs: stream computing on graphics hardware
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DOI：
10.1145/3596711.3596716
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发表时间：
2004-08
期刊：
影响因子：
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通讯作者：
I. Buck;Theresa Foley;D. Horn;J. Sugerman;Kayvon Fatahalian;Mike Houston;P. Hanrahan
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文献类型：
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作者：
I. Buck;Theresa Foley;D. Horn;J. Sugerman;Kayvon Fatahalian;Mike Houston;P. Hanrahan
在本文中，我们提出了布鲁克的GPU，可编程图形硬件上的通用计算系统。Brook扩展了C语言，使其包含简单的数据并行结构，从而可以将GPU用作流协处理器。我们提出了一个编译器和运行时系统，抽象和虚拟化的图形硬件的许多方面。此外，我们还分析了与CPU相比，GPU作为计算引擎的有效性，以确定对于特定算法，GPU何时可以优于CPU。我们评估我们的系统与五个应用程序，SAXPY和SGEMV BLAS运营商，图像分割，FFT和射线跟踪。对于这些应用程序，我们证明了我们的布鲁克实现执行的速度比手写的GPU代码快7倍。
In this paper, we present Brook for GPUs, a system for general-purpose computation on programmable graphics hardware. Brook extends C to include simple data-parallel constructs, enabling the use of the GPU as a streaming co-processor. We present a compiler and runtime system that abstracts and virtualizes many aspects of graphics hardware. In addition, we present an analysis of the effectiveness of the GPU as a compute engine compared to the CPU, to determine when the GPU can outperform the CPU for a particular algorithm. We evaluate our system with five applications, the SAXPY and SGEMV BLAS operators, image segmentation, FFT, and ray tracing. For these applications, we demonstrate that our Brook implementations perform comparably to hand-written GPU code and up to seven times faster than their CPU counterparts.