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Data Transfer Problems at the Host-Computer Level and Methods to Improve the Performance of Computations on Heterogeneous Systems

机译:主机计算机级别的数据传输问题和提高异构系统计算性能的方法

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In theory, graphics processing units largely exceed central processing units by the degree of performance. But in order to load the GPU with computing tasks to the boundary levels of its maximum performance, the task has to be divided into streams. The number of streams should be comparable to or, to some extent, exceed the value of stream processors of the GPU. Nowadays, modern graphics cards have dozens of thousands of streaming processors. This means that the task of ensuring the division into streams in computation of a sufficient degree of the GPU utilization can be either impossible or very difficult, and the solution to this problem is a "weak point" of the whole method of using the GPU, and offsets its advantages in comparison with the CPU. This scientific article is devoted to this problem.
机译:从理论上讲,图形处理单元主要超过中央处理单元。 但是为了将GPU加载到其最大性能的边界水平的计算任务,必须将任务分为流。 流的数量应与在某种程度上超过GPU的流处理器的值相当。 如今,现代图形卡有几十个媒体处理器。 这意味着在计算足够程度的GPU利用时确保划分的任务可以是不可能的或非常困难的,并且对这个问题的解决方案是使用GPU的整个方法的“弱点”, 与CPU相比,抵消其优点。 这个科学文章致力于这个问题。

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