问题描述
我是CUDA编程的新手，我正在处理一个机器上需要多个GPU的问题。我理解，为了更好的图形编程，多个GPU需要通过SLI进行组合。但是，对于CUDA编程，我还需要通过SLI来组合GPU？
I am new to CUDA programming, and I am working on a problem that requires multiple GPUs in one machine. I understand that for better graphics programming multiple GPUs need to be combined via SLI. However, for CUDA programming do I need to combine GPUs via SLI as well?
推荐答案
不，一般来说，如果计划使用GPU进行计算而不是纯图形应用程序，则可以使用SLI。您将能够从CUDA程序中访问作为分立设备的两个GPU。注意，您需要在GPU之间明确地划分工作。
No, in general you don't want to use SLI if you plan on using the GPUs for compute instead of pure graphics applications. You will be able to access both GPUs as discrete devices from within your CUDA program. Note that you will need to explicitly divide work between the GPUs.
我没有解释为什么SLI不适合计算应用程序，但它是我的在Nvidia论坛上阅读，并在IRC频道中听到其他人的意见。
I don't have an explanation for why SLI isn't desirable for compute applications, but it's what I've read on the Nvidia forums and heard from others in IRC channels.
这篇关于SLI适用于多个GPU的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！