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Theano for GPU，无需使用CUDA或使用CUDA解决方法

[英]Theano for GPU without use of CUDA or using a CUDA workaround

原文 2016-06-30 23:47:02 0 1 python/ cuda/ gpu/ theano/ theano-cuda

I have an Intel Graphics Card (Intel(R) HD Graphics 520, also am on Windows 10) and as far as I know I can't use CUDA unless I have a NVIDIA GPU. 我有一个Intel图形卡（Intel®HD Graphics 520，也位于Windows 10上），据我所知，除非拥有NVIDIA GPU，否则我将无法使用CUDA。 The purpose is to use Theano's GPU capabilities (for deep learning which is why I need GPU power). 目的是使用Theano的GPU功能（用于深度学习，这就是为什么我需要GPU功能）。

Is there a workaround that somehow allows me to use CUDA with my current GPU? 是否有一种解决方法可以使我以当前的GPU使用CUDA？
If not is there another API that I can use with my current GPU for Theano (in Python 2.7)? 如果没有，我可以在当前的Theano GPU中使用另一个API（在Python 2.7中）？
Or as a last option, using another language entirely, such as Java that has an API that allows for GPU use that I can use? 还是作为最后一个选择，完全使用另一种语言，例如Java，它具有允许我使用的GPU使用的API？

Figuring this out would be very helpful, because even though I just started with deep learning, I will probably get to the point where I need GPU parallel processing power to get results without waiting days at a minimum. 弄清楚这一点将非常有帮助，因为即使我只是从深度学习开始，我也可能会达到需要GPU并行处理能力来获得结果而无需最少等待几天的地步。

1 个解决方案

In order: 为了：

No. You must have a supported NVIDIA GPU to use CUDA. 否。您必须具有受支持的NVIDIA GPU才能使用CUDA。
As pointed out in comments, there is an alternative backend for Theano which uses OpenCL and which might work on your GPU 正如评论中指出的那样，Theano有一个备用后端，该后端使用OpenCL，并且可能在您的GPU上运行
Intel support OpenCL on your GPU, so any language bindings for the OpenCL APIs, or libraries with in-built OpenCL would be a possible solution in this case 英特尔在您的GPU上支持OpenCL，因此在这种情况下，可能会使用任何针对OpenCL API的语言绑定或具有内置OpenCL的库

[This answer has been assembled from comments and added as a community wiki entry in order to get it off the unanswered queue for the CUDA tag]. [此答案已从注释中收集并添加为社区Wiki条目，以使其脱离CUDA标签的未答复队列]。