如何让 tensorflow 在具有 2.x 能力的 GPU 上运行? [英] How can I make tensorflow run on a GPU with capability 2.x?
问题描述
我已在 Linux Ubuntu 16.04 上成功安装了 tensorflow (GPU)，并进行了一些小改动以使其与新的 Ubuntu LTS 版本兼容.
I've successfully installed tensorflow (GPU) on Linux Ubuntu 16.04 and made some small changes in order to make it work with the new Ubuntu LTS release.
但是，我认为(谁知道为什么)我的 GPU 满足了大于 3.5 的计算能力的最低要求.情况并非如此，因为我的 GeForce 820M 只有 2.1.有没有办法让 tensorflow GPU 版本与我的 GPU 一起工作?
However, I thought (who knows why) that my GPU met the minimum requirement of a compute capability greater than 3.5. That was not the case since my GeForce 820M has just 2.1. Is there a way of making tensorflow GPU version working with my GPU?
我问这个问题是因为显然没有办法让 tensorflow GPU 版本在 Ubuntu 16.04 上运行，但是通过搜索互联网我发现情况并非如此，而且如果不是因为这个不满足的要求，我确实让它几乎可以工作.现在我想知道 GPU 计算能力的这个问题是否也可以解决.
I am asking this question since apparently there was no way of making tensorflow GPU version working on Ubuntu 16.04 but by searching the internet I found out that was not the case and indeed I made it almost work were it not for this unsatisfied requirement. Now I am wondering if this issue with GPU compute capability could be fixed as well.
推荐答案
最近的 GPU 版本的 tensorflow 需要计算能力 3.5 或更高(并使用 cuDNN 访问 GPU.
Recent GPU versions of tensorflow require compute capability 3.5 or higher (and use cuDNN to access the GPU.
cuDNN 还需要 cc3.0 或更高版本的 GPU:
使用 Pascal、Kepler、Maxwell、Tegra K1 或 Tegra X1 GPU 的 Windows、Linux 和 MacOS 系统支持 cuDNN.
cuDNN is supported on Windows, Linux and MacOS systems with Pascal, Kepler, Maxwell, Tegra K1 or Tegra X1 GPUs.
- 开普勒 = cc3.x
- 麦克斯韦 = cc5.x
- 帕斯卡 = cc6.x
- TK1 = cc3.2
- TX1 = cc5.3
cuDNN 不支持 Fermi GPU(cc2.0、cc2.1).
Fermi GPUs (cc2.0, cc2.1) are not supported by cuDNN.
cuDNN 也不支持较旧的 GPU(例如计算能力 1.x).
Older GPUs (e.g. compute capability 1.x) are also not supported by cuDNN.
请注意，从来没有任何版本的 cuDNN 或任何官方支持低于 cc3.0 的 NVIDIA GPU 的 TF 版本.cuDNN 初始版本需要 cc3.0 GPU，TF 初始版本需要 cc3.0 GPU.
Note that there has never been either a version of cuDNN or any version of TF that officially supported NVIDIA GPUs less than cc3.0. The initial version of cuDNN started out by requiring cc3.0 GPUs, and the initial version of TF started out by requiring cc3.0 GPUs.
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