xgboost/tests/ci_build/Dockerfile.gpu_build
Philip Hyunsu Cho 88b64c8162
Ensure that configured dmlc/build_config.h is picked up by Rabit and XGBoost (#5514)
* Ensure that configured header (build_config.h) from dmlc-core is picked up by Rabit and XGBoost

* Check which Rabit target is being used

* Use CMake 3.13 in all Jenkins tests

* Upgrade CMake in Travis CI

* Install CMake using Kitware installer

* Remove existing CMake (3.12.4)
2020-04-11 23:48:28 -07:00

59 lines
2.5 KiB
Docker

ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-devel-centos6
# Environment
ENV DEBIAN_FRONTEND noninteractive
ENV DEVTOOLSET_URL_ROOT http://mirror.centos.org/centos/6/sclo/x86_64/rh/devtoolset-4
# Install all basic requirements
RUN \
yum -y update && \
yum install -y tar unzip wget xz git centos-release-scl yum-utils && \
yum-config-manager --enable centos-sclo-rh-testing && \
yum -y update && \
yum install -y $DEVTOOLSET_URL_ROOT/devtoolset-4-gcc-5.3.1-6.1.el6.x86_64.rpm \
$DEVTOOLSET_URL_ROOT/devtoolset-4-gcc-c++-5.3.1-6.1.el6.x86_64.rpm \
$DEVTOOLSET_URL_ROOT/devtoolset-4-binutils-2.25.1-8.el6.x86_64.rpm \
$DEVTOOLSET_URL_ROOT/devtoolset-4-runtime-4.1-3.sc1.el6.x86_64.rpm \
$DEVTOOLSET_URL_ROOT/devtoolset-4-libstdc++-devel-5.3.1-6.1.el6.x86_64.rpm && \
# Python
wget https://repo.continuum.io/miniconda/Miniconda3-4.5.12-Linux-x86_64.sh && \
bash Miniconda3-4.5.12-Linux-x86_64.sh -b -p /opt/python && \
# CMake
wget -nv -nc https://cmake.org/files/v3.13/cmake-3.13.0-Linux-x86_64.sh --no-check-certificate && \
bash cmake-3.13.0-Linux-x86_64.sh --skip-license --prefix=/usr
# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
RUN \
export CUDA_SHORT=`echo $CUDA_VERSION | egrep -o '[0-9]+\.[0-9]'` && \
export NCCL_VERSION=2.4.8-1 && \
wget https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
yum -y update && \
yum install -y libnccl-${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-devel-${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-static-${NCCL_VERSION}+cuda${CUDA_SHORT} && \
rm -f nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm;
ENV PATH=/opt/python/bin:$PATH
ENV CC=/opt/rh/devtoolset-4/root/usr/bin/gcc
ENV CXX=/opt/rh/devtoolset-4/root/usr/bin/c++
ENV CPP=/opt/rh/devtoolset-4/root/usr/bin/cpp
# Install Python packages
RUN \
pip install numpy pytest scipy scikit-learn wheel kubernetes urllib3==1.22
ENV GOSU_VERSION 1.10
# Install lightweight sudo (not bound to TTY)
RUN set -ex; \
wget -O /usr/local/bin/gosu "https://github.com/tianon/gosu/releases/download/$GOSU_VERSION/gosu-amd64" && \
chmod +x /usr/local/bin/gosu && \
gosu nobody true
# Default entry-point to use if running locally
# It will preserve attributes of created files
COPY entrypoint.sh /scripts/
WORKDIR /workspace
ENTRYPOINT ["/scripts/entrypoint.sh"]