主机级数据传输问题及提高异构系统计算性能的方法

A. Bashkirov, V. Glotov, N. Astakhov, A. A. Pirogov, Anastasia Kalyadina, T. Glotova
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引用次数: 0

摘要

理论上,图形处理单元在性能上大大超过中央处理单元。但是,为了使GPU的计算任务加载到其最大性能的边界水平,必须将任务划分为流。流的数量应该与GPU的流处理器数量相当,或者在某种程度上超过GPU的流处理器数量。如今,现代显卡有成千上万的流处理器。这意味着确保在计算中划分足够程度的GPU利用率的流的任务要么是不可能的,要么是非常困难的,解决这个问题是使用GPU的整个方法的“弱点”,并且抵消了它与CPU相比的优势。这篇科学文章专门讨论这个问题。关键词:处理器,显卡,伪随机数
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Data Transfer Problems at the Host-Computer Level and Methods to Improve the Performance of Computations on Heterogeneous Systems
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. Keywords— processor, video card, pseudorandom number
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