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Graphics hardware for scientific computation

机译:用于科学计算的图形硬件

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摘要

Modern Graphics Processing Units (GPUs) commonly found in today's PCs feature multiple processing units and can be used for general purpose computations and in particular, parallel numerical algorithms. But the available level of abstraction is still very low. Typically, GPU programs are written in assembly language. In this paper, the architecture which is still tightly coupled to the rasterisation algorithm that GPUs are originally meant to implement, and some of the algorithms efficiently implemented on GPUs so far, will be presented. The strengths and weaknesses of GPUs and approaches towards the goal of an easily programmable GPU are presented.
机译:当今PC中常见的现代图形处理单元(GPU)具有多个处理单元,可用于通用计算,尤其是并行数值算法。但是抽象的可用级别仍然很低。通常,GPU程序是用汇编语言编写的。在本文中,将介绍仍与GPU原本打算实现的光栅化算法紧密结合的体系结构,以及到目前为止在GPU上有效实现的一些算法。介绍了GPU的优缺点和实现易于编程的GPU的方法。

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