CUDA 在 Amazon EC2 P2 实例上运行的深度学习 AMI (DLAMI) 上不可用

CUDA 在 Amazon EC2 P2 实例上运行的深度学习 AMI (DLAMI) 上不可用

我正在运行Ubuntu 18.04 深度学习 AMI (DLAMI)在 AWS 上,并尝试在p2.xlargeEC2 实例上运行它,但 CUDA 在我的 Python 解释器中不可用。我假设 CUDA 可以开箱即用,因为它是一个 AMI,据说是为与 torch/CUDA 一起使用而设计的。

pytorch_latest_p37我正在尝试在预装 DLAMI 的 conda 环境中运行我的代码。它使用 Python3.7,并附带使用 CUDA 11.0 构建的 PyTorch 1.7.1:

ubuntu@ip-111-21-33-212:~$ source activate pytorch_latest_p37

nvidia-smi和的输出nvcc似乎都表明 CUDA 已安装:

(pytorch_latest_p37) ubuntu@ip-111-21-33-212:~$ nvidia-smi
Sun Jul 18 07:51:09 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.119.03   Driver Version: 450.119.03   CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  Tesla K80           On   | 00000000:00:1E.0 Off |                    0 |
| N/A   32C    P8    30W / 149W |      0MiB / 11441MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+


(pytorch_latest_p37) ubuntu@ip-111-21-33-212:~$ nvcc --version                  nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Mon_Oct_12_20:09:46_PDT_2020
Cuda compilation tools, release 11.1, V11.1.105
Build cuda_11.1.TC455_06.29190527_0

但在 ipython 中torch.cuda.is_available()返回时false,我收到错误消息,指出 torch 未使用 CUDA 支持进行编译:

(pytorch_latest_p37) ubuntu@ip-111-21-33-212:~$ ipython
Python 3.9.5 (default, Jun  4 2021, 12:28:51)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.22.0 -- An enhanced Interactive Python. Type '?' for help.

In [1]: import torch

In [2]: torch.cuda.is_available()
Out[2]: False

In [3]: torch.zeros(1).cuda()
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-2-0904fac96cba> in <module>
----> 1 torch.zeros(1).cuda()

~/anaconda3/envs/pytorch_latest_p37/lib/python3.9/site-packages/torch/cuda/__init__.py in _lazy_init()
    164                 "Cannot re-initialize CUDA in forked subprocess. " + msg)
    165         if not hasattr(torch._C, '_cuda_getDeviceCount'):
--> 166             raise AssertionError("Torch not compiled with CUDA enabled")
    167         if _cudart is None:
    168             raise AssertionError(

AssertionError: Torch not compiled with CUDA enabled

这里发生了什么?我需要做什么才能让 CUDA 在 P2/P3 实例上运行?

谢谢!

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