Public | Automated Build

Last pushed: 2 years ago
Short Description
Caffe with cuda 7.0.28 and scipy stack
Full Description

caffegpudockeralt

Docker to do caffe, cuda, python

Install docker:

sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys 36A1D7869245C8950F966E92D8576A8BA88D21E9; sudo sh -c "echo deb https://get.docker.com/ubuntu docker main > /etc/apt/sources.list.d/docker.list"; sudo apt-get update; sudo apt-get install lxc-docker

Pull from dockerhub and run docker instance:

sudo docker pull trackdr/caffegpudockeralt; cd /usr/local/cuda-7.0/samples/1_Utilities/deviceQuery; make; /home/ubuntu/NVIDIA_CUDA-7.0_Samples/bin/x86_64/linux/release/deviceQuery; DOCKER_NVIDIA_DEVICES="--device /dev/nvidia0:/dev/nvidia0 --device /dev/nvidiactl:/dev/nvidiactl --device /dev/nvidia-uvm:/dev/nvidia-uvm"; sudo docker run -ti $DOCKER_NVIDIA_DEVICES trackdr/gpucaffedockeralt /bin/bash; sudo docker ps

OR Build docker instance and run docker instance:

git clone https://github.com/TrackDR/caffegpudockeralt;
sudo docker build caffegpudockeralt;
cd /usr/local/cuda-7.0/samples/1_Utilities/deviceQuery;
make;
/home/ubuntu/NVIDIA_CUDA-7.0_Samples/bin/x86_64/linux/release/deviceQuery;
DOCKER_NVIDIA_DEVICES="--device /dev/nvidia0:/dev/nvidia0 --device /dev/nvidiactl:/dev/nvidiactl --device /dev/nvidia-uvm:/dev/nvidia-uvm";
sudo docker run -ti $DOCKER_NVIDIA_DEVICES gpucaffedockeralt /bin/bash;
sudo docker ps

Download samples for cuda:

wget http://developer.download.nvidia.com/compute/cuda/7_0/Prod/local_installers/cuda_7.0.28_linux.run;
chmod +x cuda_7.0.28_linux.run; ./cuda_7.0.28_linux.run -extract=pwd; ./cuda-samples-linux-*.run -noprompt; cd /usr/local/cuda-7.0/samples/1_Utilities/deviceQuery; make; ../../bin/x86_64/linux/release/deviceQuery

cd /opt/caffe; make runtest

List containers:

sudo docker ps

Attach to instance:

sudo docker exec -it containerid bash

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Owner
trackdr
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