th -e "require 'cutorch'; require 'cunn'; print(cutorch)"
/root/torch/install/share/lua/5.1/trepl/init.lua:378: cuda runtime error (38) : no CUDA-capable device is detected at /tmp/luarocks_cutorch-scm-1-4711/cutorch/lib/THC/THCGeneral.c:16
# lsmod | grep -i nvidia
nvidia_uvm 35066 0
nvidia 10540162 1 nvidia_uvm
drm 303102 1 nvidia
# ls -alh /dev | grep -i nvidia
crw-rw-rw- 1 root root 251, 0 Nov 22 20:06 nvidia-uvm
crw-rw-rw- 1 root root 195, 0 Nov 22 20:06 nvidia0
crw-rw-rw- 1 root root 195, 255 Nov 22 20:06 nvidiactl
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$ wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_7.5-18_amd64.deb
$ sudo dpkg -i cuda-repo-ubuntu1404_7.5-18_amd64.deb
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I'll try re-installing cuda inside the docker container to see if that fixes it.
$ wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_7.5-18_amd64.deb
$ sudo dpkg -i cuda-repo-ubuntu1404_7.5-18_amd64.
deb
$ sudo apt-get update
$ sudo apt-get upgrade -y
$ sudo apt-get install -y opencl-headers build-essential protobuf-compiler \
libprotoc-dev libboost-all-dev libleveldb-dev hdf5-tools libhdf5-serial-dev \
libopencv-core-dev libopencv-highgui-dev libsnappy-dev libsnappy1 \
libatlas-base-dev cmake libstdc++6-4.8-dbg libgoogle-glog0 libgoogle-glog-dev \
libgflags-dev liblmdb-dev git python-pip gfortran
$ sudo apt-get clean
$ sudo apt-get install -y linux-image-extra-`uname -r` linux-headers-`uname -r` linux-image-`uname -r`
$ sudo apt-get install -y cuda
th -e "require 'cutorch'; require 'cunn'; print(cutorch)"
{
getStream : function: 0x4054b760
getDeviceCount : function: 0x408bca58
.. etc
}
On Sun, Nov 22, 2015 at 2:33 PM, torch7 on behalf of smth chntla <tor...@googlegroups.com> wrote:
On docker, there's a restriction for CUDA that the NVIDIA driver installed inside docker has to match the NVIDIA driver on the host machine. If it doesn't match, this error occurs.
On Sun, Nov 22, 2015 at 4:02 PM, Traun Leyden via torch7 <torch7+APn2wQe4YpRsrV7DfLBb5DzJfLp4Sweec5oM6W7nE2tY-HpccjbjoqIpg@googlegroups.com> wrote:
I'm installing CUDA 6.5 + Torch on an AWS GPU instance using these instructions, but when I run:
th -e "require 'cutorch'; require 'cunn'; print(cutorch)"I'm getting this error:
/root/torch/install/share/lua/5.1/trepl/init.lua:378: cuda runtime error (38) : no CUDA-capable device is detected at /tmp/luarocks_cutorch-scm-1-4711/cutorch/lib/THC/THCGeneral.c:16OTOH, if I follow the same instructions above but skip the docker stuff and install directly on the Host OS, it works.Anyone have any idea how to debug this or what the "missing link" might be?Inside the docker container, I can see the kernel module and the devices:
# lsmod | grep -i nvidia
nvidia_uvm 35066 0
nvidia 10540162 1 nvidia_uvm
drm 303102 1 nvidia
# ls -alh /dev | grep -i nvidia
crw-rw-rw- 1 root root 251, 0 Nov 22 20:06 nvidia-uvm
crw-rw-rw- 1 root root 195, 0 Nov 22 20:06 nvidia0
crw-rw-rw- 1 root root 195, 255 Nov 22 20:06 nvidiactl
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