cuda内存中的Gpu应用程序

Khoirudin, Jiang Shun-liang
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引用次数: 11

摘要

如今现代计算机GPU(图形处理单元)被广泛用于提高计算机的性能,这基本上是针对图形计算的GPU,现在不仅用于计算图形的目的,而且还用于其他应用。此外,图形处理单元(GPU)具有高计算能力和低价格的特点。使用CUDA软件可以将该器件视为SIMD处理器阵列。本文讨论了基于reduce内核的GPU应用、CUDA内存和高效CUDA内存。高性能GPU应用需要在流多处理器(SM)内部重用数据。原因是板载全局内存不够快,无法满足GPU上所有流多处理器的需求。此外,CUDA公开了SM中的内存空间,并提供了可配置的缓存,为开发人员提供了最大的数据重用机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GPU APPLICATION IN CUDA MEMORY
Nowadays modern computer GPU (Graphic Processing Unit) became widely used to improve the performance of a computer, which is basically for the GPU graphics calculations, are now used not only for the purposes of calculating the graphics but also for other application. In addition, Graphics Processing Unit (GPU) has high computation and low price. This device can be treat as an array of SIMD processor using CUDA software. This paper talks about GPU application, CUDA memory and efficient CUDA memory using Reduction kernel. High-performance GPU application requires reuse of data inside the streaming multiprocessor (SM). The reason is that onboard global memory is simply not fast enough to meet the needs of all the streaming multiprocessor on the GPU. In addition, CUDA exposes the memory space within the SM and provides configurable caches to give the developer the greatest opportunity of data reuse.
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