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Support building XGBoost with CUDA 11 (#5808)

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* Change serialization test.
* Add CUDA 11 tests on Linux CI.

Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Andy Adinets
2020-07-20 01:58:41 +02:00
committed by GitHub
parent ac9136ee49
commit b3d2e7644a
7 changed files with 128 additions and 75 deletions
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tests/ci_build/Dockerfile.gpu_build
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@@ -1,53 +1,30 @@
ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-devel-centos6
FROM nvidia/cuda:$CUDA_VERSION-devel-ubuntu16.04
ARG CUDA_VERSION
# Environment
ENV DEBIAN_FRONTEND noninteractive
ENV DEVTOOLSET_URL_ROOT http://vault.centos.org/6.9/sclo/x86_64/rh/devtoolset-4/
SHELL ["/bin/bash", "-c"] # Use Bash as shell
# 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 -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3.sh -b -p /opt/python && \
apt-get update && \
apt-get install -y tar unzip wget bzip2 libgomp1 git build-essential doxygen graphviz llvm libasan2 libidn11 liblz4-dev ninja-build && \
# 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 && \
# Ninja
mkdir -p /usr/local && \
cd /usr/local/ && \
wget -nv -nc https://github.com/ninja-build/ninja/archive/v1.10.0.tar.gz --no-check-certificate && \
tar xf v1.10.0.tar.gz && mv ninja-1.10.0 ninja && rm -v v1.10.0.tar.gz && \
cd ninja && \
python ./configure.py --bootstrap
# Python
wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
bash Miniconda3.sh -b -p /opt/python
# 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${CUDA_SHORT} && \
rm -f nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm;
export NCCL_VERSION=2.7.5-1 && \
apt-get update && \
apt-get install -y --allow-downgrades --allow-change-held-packages libnccl2=${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-dev=${NCCL_VERSION}+cuda${CUDA_SHORT}
ENV PATH=/opt/python/bin:/usr/local/ninja:$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 PATH=/opt/python/bin:$PATH
ENV GOSU_VERSION 1.10