bcb15a980f
* Hide C++ symbols from dmlc-core (#6188) * Up version to 1.2.1 * Fix lint * [CI] Fix Docker build for CUDA 11 (#6202) * Update Dockerfile.gpu
64 lines
2.8 KiB
Docker
64 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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# Install all basic requirements
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RUN \
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yum -y update && \
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yum install -y tar unzip wget xz git centos-release-scl yum-utils java-1.8.0-openjdk-devel && \
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yum-config-manager --enable centos-sclo-rh-testing && \
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yum -y update && \
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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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# CMake
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wget -nv -nc https://cmake.org/files/v3.13/cmake-3.13.0-Linux-x86_64.sh --no-check-certificate && \
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bash cmake-3.13.0-Linux-x86_64.sh --skip-license --prefix=/usr && \
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# Maven
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wget https://archive.apache.org/dist/maven/maven-3/3.6.1/binaries/apache-maven-3.6.1-bin.tar.gz && \
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tar xvf apache-maven-3.6.1-bin.tar.gz -C /opt && \
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ln -s /opt/apache-maven-3.6.1/ /opt/maven
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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 $CUDA_VERSION_ARG | egrep -o '[0-9]+\.[0-9]'` && \
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export NCCL_VERSION=2.4.8-1 && \
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wget https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
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rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
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yum -y update && \
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yum install -y libnccl-${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-devel-${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-static-${NCCL_VERSION}+cuda${CUDA_SHORT} && \
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rm -f nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm;
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ENV PATH=/opt/python/bin:/opt/maven/bin:$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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# Install Python packages
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RUN \
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pip install numpy pytest scipy scikit-learn wheel kubernetes urllib3==1.22 awscli
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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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