65 lines
2.8 KiB
Docker
65 lines
2.8 KiB
Docker
ARG CUDA_VERSION_ARG
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FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-centos6
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ARG CUDA_VERSION_ARG
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# Environment
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ENV DEBIAN_FRONTEND noninteractive
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ENV DEVTOOLSET_URL_ROOT http://vault.centos.org/6.9/sclo/x86_64/rh/devtoolset-4/
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COPY CentOS-Base.repo /etc/yum.repos.d/
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# Install all basic requirements
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RUN \
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yum install -y epel-release && \
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yum -y update && \
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yum install -y tar unzip wget xz git patchelf && \
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yum install -y $DEVTOOLSET_URL_ROOT/devtoolset-4-gcc-5.3.1-6.1.el6.x86_64.rpm \
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$DEVTOOLSET_URL_ROOT/devtoolset-4-gcc-c++-5.3.1-6.1.el6.x86_64.rpm \
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$DEVTOOLSET_URL_ROOT/devtoolset-4-binutils-2.25.1-8.el6.x86_64.rpm \
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$DEVTOOLSET_URL_ROOT/devtoolset-4-runtime-4.1-3.sc1.el6.x86_64.rpm \
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$DEVTOOLSET_URL_ROOT/devtoolset-4-libstdc++-devel-5.3.1-6.1.el6.x86_64.rpm && \
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# Python
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wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
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bash Miniconda3.sh -b -p /opt/python && \
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/opt/python/bin/python -m pip install auditwheel && \
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# CMake
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wget -nv -nc https://cmake.org/files/v3.14/cmake-3.14.0-Linux-x86_64.sh --no-check-certificate && \
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bash cmake-3.14.0-Linux-x86_64.sh --skip-license --prefix=/usr && \
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# Ninja
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mkdir -p /usr/local && \
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cd /usr/local/ && \
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wget -nv -nc https://github.com/ninja-build/ninja/archive/v1.10.0.tar.gz --no-check-certificate && \
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tar xf v1.10.0.tar.gz && mv ninja-1.10.0 ninja && rm -v v1.10.0.tar.gz && \
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cd ninja && \
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/opt/python/bin/python ./configure.py --bootstrap
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# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
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RUN \
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export CUDA_SHORT=`echo $CUDA_VERSION_ARG | grep -o -E '[0-9]+\.[0-9]'` && \
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export NCCL_VERSION=2.4.8-1 && \
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wget https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
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rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
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yum -y update && \
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yum install -y libnccl-${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-devel-${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-static-${NCCL_VERSION}+cuda${CUDA_SHORT} && \
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rm -f nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm;
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ENV PATH=/opt/python/bin:/usr/local/ninja:$PATH
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ENV CC=/opt/rh/devtoolset-4/root/usr/bin/gcc
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ENV CXX=/opt/rh/devtoolset-4/root/usr/bin/c++
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ENV CPP=/opt/rh/devtoolset-4/root/usr/bin/cpp
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ENV GOSU_VERSION 1.10
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# Install lightweight sudo (not bound to TTY)
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RUN set -ex; \
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wget -O /usr/local/bin/gosu "https://github.com/tianon/gosu/releases/download/$GOSU_VERSION/gosu-amd64" && \
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chmod +x /usr/local/bin/gosu && \
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gosu nobody true
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# Default entry-point to use if running locally
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# It will preserve attributes of created files
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COPY entrypoint.sh /scripts/
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WORKDIR /workspace
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ENTRYPOINT ["/scripts/entrypoint.sh"]
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