CUDA cudaErrorInsufficientDriver在d中运行CuFFT时出错

Question

我在docker做一些袖口动作，遇到了一些问题。我使用以下Dockerfile。你知道吗

FROM nvidia/cuda:9.1-runtime-ubuntu16.04
ENV NVIDIA_VISIBLE_DEVICES all
ENV LD_LIBRARY_PATH /usr/local/cuda-9.1/lib64/

FROM python:3.7
COPY --from=0 /usr/local/cuda-9.1 /usr/local/cuda-9.1
ENV VIRTUAL_ENV=/opt/venv
ENV PATH="/opt/venv:$PATH"
RUN pip install numpy
RUN apt update && \
    apt-get -y install gcc && \
    apt-get -y install apt-utils && \
    apt-get -y install g++ && \
    apt-get -y install pciutils && \
    apt-get -y install libc6

ADD helmsolver /helmsolver
CMD ls /usr && ls /usr/local
CMD dpkg -l | grep -i cuda
CMD cd helmsolver && bash tests.sh

为了构建和运行docker，我使用了这样的命令。你知道吗

docker build -t helm .
docker run --gpus all helm

我可以在主机上运行我的代码，但是在docker中运行之后，错误35（cudaErrorInsufficientDriver）出现在这种类型的代码cudaMalloc((void**)&d_array, memsize)。我的代码有什么问题，或者只是缺少了一些.so文件？ 这是我的CUDA，docker，nvidia smi版本

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Nov__3_21:07:56_CDT_2017
Cuda compilation tools, release 9.1, V9.1.85

Docker version 19.03.4

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.67       Driver Version: 418.67       CUDA Version: N/A      |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce GT 640      On   | 00000000:01:00.0 N/A |                  N/A |
| 40%   36C    P8    N/A /  N/A |     48MiB /  4035MiB |     N/A      Default |
+-------------------------------+----------------------+----------------------+
|   1  GeForce GTX 760     On   | 00000000:02:00.0 N/A |                  N/A |
| 17%   36C    P8    N/A /  N/A |      1MiB /  4037MiB |     N/A      Default |
+-------------------------------+----------------------+----------------------+

Answer 1

添加NVIDIA_DRIVER_CAPABILITIES compute, utility作为ENV解决了这个问题。你知道吗