tool/docker/devel/centos6/cuda10/Dockerfile.manylinux2014 - singa - Git at Google

 # Licensed to the Apache Software Foundation (ASF) under one
 # or more contributor license agreements.  See the NOTICE file
 # distributed with this work for additional information
 # regarding copyright ownership.  The ASF licenses this file
 # to you under the Apache License, Version 2.0 (the
 # "License"); you may not use this file except in compliance
 # with the License.  You may obtain a copy of the License at
 #
 #     http://www.apache.org/licenses/LICENSE-2.0
 #
 # Unless required by applicable law or agreed to in writing, software
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.


 # The latest tag uses gcc 9, which is too high for nvcc.
 # The following tag uses gcc 8, which works with nvcc.
 FROM quay.io/pypa/manylinux2014_x86_64:2020-05-01-b37d76b

 # install dependencies
 RUN yum install -y \
     protobuf-devel \
     openblas-devel \
     # git \
     wget \
     openssh-server \
     pcre-devel \
     cmake \
     && yum clean all \
     && rm -rf /var/cache/yum/*

 # install glog into /usr/local/include/glog /usr/local/lib
 RUN wget https://github.com/google/glog/archive/v0.3.5.tar.gz -P /tmp/\
     && tar zxf /tmp/v0.3.5.tar.gz  -C /tmp/ \
     && cd /tmp/glog-0.3.5 \
     && ./configure && make && make install && cd .. && rm -rf glog-0.3.5

 # install dnnl into /usr/local/include  /usr/local/lib
 RUN wget https://github.com/intel/mkl-dnn/releases/download/v1.1/dnnl_lnx_1.1.0_cpu_gomp.tgz -P /tmp/ \
     && tar zxf /tmp/dnnl_lnx_1.1.0_cpu_gomp.tgz  -C /tmp/ \
     && cp -r -H /tmp/dnnl_lnx_1.1.0_cpu_gomp/lib/lib* /usr/local/lib/ \
     && cp -r -H /tmp/dnnl_lnx_1.1.0_cpu_gomp/include/* /usr/local/include/  \
     && rm -rf /tmp/dnnl_lnx_1.1.0_cpu_gomp
 # ENV DNNL_ROOT /root/dnnl_lnx_1.1.0_cpu_gomp/

 # install swig into /usr/local/bin
 RUN wget http://prdownloads.sourceforge.net/swig/swig-3.0.12.tar.gz -P /tmp/ \
     && tar zxf /tmp/swig-3.0.12.tar.gz -C /tmp/ \
     && cd /tmp/swig-3.0.12 && ./configure && make && make install && cd .. && rm -rf swig-3.0.12

 # numpy and python versions should be matched;
 # twine works for all python versions
 RUN /opt/python/cp36-cp36m/bin/pip install numpy twine
 RUN /opt/python/cp37-cp37m/bin/pip install numpy
 RUN /opt/python/cp38-cp38/bin/pip install numpy

 # install cuda and cudnn
 # Refer to https://gitlab.com/nvidia/container-images/cuda/-/tree/master/dist for other cuda and cudnn versions
 # 10.2-base-centos7
 RUN NVIDIA_GPGKEY_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \
     curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/7fa2af80.pub | sed '/^Version/d' > /etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA && \
     echo "$NVIDIA_GPGKEY_SUM  /etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA" | sha256sum -c --strict  -
 COPY cuda.repo /etc/yum.repos.d/cuda.repo
 ENV CUDA_VERSION 10.2.89
 ENV CUDA_PKG_VERSION 10-2-$CUDA_VERSION-1
 # For libraries in the cuda-compat-* package: https://docs.nvidia.com/cuda/eula/index.html#attachment-a
 RUN yum install -y \
     cuda-cudart-$CUDA_PKG_VERSION \
     cuda-compat-10-2 \
     && ln -s cuda-10.2 /usr/local/cuda && \
     rm -rf /var/cache/yum/*

 # nvidia-docker 1.0
 RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
     echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
 ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64:$LD_LIBRARY_PATH

 # nvidia-container-runtime
 ENV NVIDIA_VISIBLE_DEVICES all
 ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
 ENV NVIDIA_REQUIRE_CUDA "cuda>=10.2 brand=tesla,driver>=396,driver<397 brand=tesla,driver>=410,driver<411 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441"

 # 10.2-runtime-centos7
 RUN yum install -y \
     cuda-libraries-$CUDA_PKG_VERSION \
     cuda-nvtx-$CUDA_PKG_VERSION \
     libcublas10-10.2.2.89-1 \
     && rm -rf /var/cache/yum/*


 # 10.2-devel-centos7
 RUN yum install -y \
     cuda-nvml-dev-$CUDA_PKG_VERSION \
     cuda-command-line-tools-$CUDA_PKG_VERSION \
     cuda-cudart-dev-$CUDA_PKG_VERSION \
     cuda-libraries-dev-$CUDA_PKG_VERSION \
     cuda-minimal-build-$CUDA_PKG_VERSION \
     && rm -rf /var/cache/yum/*
 RUN yum install -y xz && NCCL_DOWNLOAD_SUM=a9ee790c3fc64b0ecbb00db92eddc1525552eda10a8656ff4b7380f66d81bda1 && \
     curl -fsSL https://developer.download.nvidia.com/compute/redist/nccl/v2.7/nccl_2.7.3-1+cuda10.2_x86_64.txz -O && \
     echo "$NCCL_DOWNLOAD_SUM  nccl_2.7.3-1+cuda10.2_x86_64.txz" | sha256sum -c - && \
     unxz nccl_2.7.3-1+cuda10.2_x86_64.txz && \
     tar --no-same-owner --keep-old-files --no-overwrite-dir -xvf  nccl_2.7.3-1+cuda10.2_x86_64.tar -C /usr/local/cuda/include/ --strip-components=2 --wildcards '*/include/*' && \
     tar --no-same-owner --keep-old-files --no-overwrite-dir -xvf  nccl_2.7.3-1+cuda10.2_x86_64.tar -C /usr/local/cuda/lib64/ --strip-components=2 --wildcards '*/lib/libnccl.so' && \
     rm -f nccl_2.7.3-1+cuda10.2_x86_64.tar && \
     ldconfig
 ENV LIBRARY_PATH /usr/local/cuda/lib64/stubs

 # 10.2-cudnn7-devel-centos7
 ENV CUDNN_VERSION 7.6.5.32
 # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
 RUN CUDNN_DOWNLOAD_SUM=600267f2caaed2fd58eb214ba669d8ea35f396a7d19b94822e6b36f9f7088c20 && \
     curl -fsSL http://developer.download.nvidia.com/compute/redist/cudnn/v7.6.5/cudnn-10.2-linux-x64-v7.6.5.32.tgz -O && \
     echo "$CUDNN_DOWNLOAD_SUM  cudnn-10.2-linux-x64-v7.6.5.32.tgz" | sha256sum -c - && \
     tar --no-same-owner -xzf cudnn-10.2-linux-x64-v7.6.5.32.tgz -C /usr/local && \
     rm cudnn-10.2-linux-x64-v7.6.5.32.tgz && \
     ldconfig

 # install nccl for distributed training
 RUN git clone https://github.com/NVIDIA/nccl.git $HOME/nccl \
     && cd $HOME/nccl \
     && git checkout v2.4.8-1 \
     && make BUILDDIR=/usr/local/ -j$(nproc) src.build \
     && rm -rf /usr/local/obj \
     && rm -rf $HOME/nccl

 # install cnmem to /usr/local/include  /usr/local/lib
 RUN git clone https://github.com/NVIDIA/cnmem.git cnmem \
     && cd cnmem && mkdir build && cd build && cmake .. && make && make install && cd ../.. && rm -rf cnmem

 # install mpich /usr/local/include   /usr/local/lib
 RUN wget http://www.mpich.org/static/downloads/3.3.2/mpich-3.3.2.tar.gz -P $HOME \
     && cd $HOME \
     && tar xfz mpich-3.3.2.tar.gz \
     && cd mpich-3.3.2 \
     && ./configure --prefix=/usr/local --disable-fortran \
     && make && make install  && cd .. && rm -rf mpich-3.3.2
	# Licensed to the Apache Software Foundation (ASF) under one
	# or more contributor license agreements. See the NOTICE file
	# distributed with this work for additional information
	# regarding copyright ownership. The ASF licenses this file
	# to you under the Apache License, Version 2.0 (the
	# "License"); you may not use this file except in compliance
	# with the License. You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.


	# The latest tag uses gcc 9, which is too high for nvcc.
	# The following tag uses gcc 8, which works with nvcc.
	FROM quay.io/pypa/manylinux2014_x86_64:2020-05-01-b37d76b

	# install dependencies
	RUN yum install -y \
	protobuf-devel \
	openblas-devel \
	# git \
	wget \
	openssh-server \
	pcre-devel \
	cmake \
	&& yum clean all \
	&& rm -rf /var/cache/yum/*

	# install glog into /usr/local/include/glog /usr/local/lib
	RUN wget https://github.com/google/glog/archive/v0.3.5.tar.gz -P /tmp/\
	&& tar zxf /tmp/v0.3.5.tar.gz -C /tmp/ \
	&& cd /tmp/glog-0.3.5 \
	&& ./configure && make && make install && cd .. && rm -rf glog-0.3.5

	# install dnnl into /usr/local/include /usr/local/lib
	RUN wget https://github.com/intel/mkl-dnn/releases/download/v1.1/dnnl_lnx_1.1.0_cpu_gomp.tgz -P /tmp/ \
	&& tar zxf /tmp/dnnl_lnx_1.1.0_cpu_gomp.tgz -C /tmp/ \
	&& cp -r -H /tmp/dnnl_lnx_1.1.0_cpu_gomp/lib/lib* /usr/local/lib/ \
	&& cp -r -H /tmp/dnnl_lnx_1.1.0_cpu_gomp/include/* /usr/local/include/ \
	&& rm -rf /tmp/dnnl_lnx_1.1.0_cpu_gomp
	# ENV DNNL_ROOT /root/dnnl_lnx_1.1.0_cpu_gomp/

	# install swig into /usr/local/bin
	RUN wget http://prdownloads.sourceforge.net/swig/swig-3.0.12.tar.gz -P /tmp/ \
	&& tar zxf /tmp/swig-3.0.12.tar.gz -C /tmp/ \
	&& cd /tmp/swig-3.0.12 && ./configure && make && make install && cd .. && rm -rf swig-3.0.12

	# numpy and python versions should be matched;
	# twine works for all python versions
	RUN /opt/python/cp36-cp36m/bin/pip install numpy twine
	RUN /opt/python/cp37-cp37m/bin/pip install numpy
	RUN /opt/python/cp38-cp38/bin/pip install numpy

	# install cuda and cudnn
	# Refer to https://gitlab.com/nvidia/container-images/cuda/-/tree/master/dist for other cuda and cudnn versions
	# 10.2-base-centos7
	RUN NVIDIA_GPGKEY_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \
	curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/7fa2af80.pub \| sed '/^Version/d' > /etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA && \
	echo "$NVIDIA_GPGKEY_SUM /etc/pki/rpm-gpg/RPM-GPG-KEY-NVIDIA" \| sha256sum -c --strict -
	COPY cuda.repo /etc/yum.repos.d/cuda.repo
	ENV CUDA_VERSION 10.2.89
	ENV CUDA_PKG_VERSION 10-2-$CUDA_VERSION-1
	# For libraries in the cuda-compat-* package: https://docs.nvidia.com/cuda/eula/index.html#attachment-a
	RUN yum install -y \
	cuda-cudart-$CUDA_PKG_VERSION \
	cuda-compat-10-2 \
	&& ln -s cuda-10.2 /usr/local/cuda && \
	rm -rf /var/cache/yum/*

	# nvidia-docker 1.0
	RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
	echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
	ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
	ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64:$LD_LIBRARY_PATH

	# nvidia-container-runtime
	ENV NVIDIA_VISIBLE_DEVICES all
	ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
	ENV NVIDIA_REQUIRE_CUDA "cuda>=10.2 brand=tesla,driver>=396,driver<397 brand=tesla,driver>=410,driver<411 brand=tesla,driver>=418,driver<419 brand=tesla,driver>=440,driver<441"

	# 10.2-runtime-centos7
	RUN yum install -y \
	cuda-libraries-$CUDA_PKG_VERSION \
	cuda-nvtx-$CUDA_PKG_VERSION \
	libcublas10-10.2.2.89-1 \
	&& rm -rf /var/cache/yum/*


	# 10.2-devel-centos7
	RUN yum install -y \
	cuda-nvml-dev-$CUDA_PKG_VERSION \
	cuda-command-line-tools-$CUDA_PKG_VERSION \
	cuda-cudart-dev-$CUDA_PKG_VERSION \
	cuda-libraries-dev-$CUDA_PKG_VERSION \
	cuda-minimal-build-$CUDA_PKG_VERSION \
	&& rm -rf /var/cache/yum/*
	RUN yum install -y xz && NCCL_DOWNLOAD_SUM=a9ee790c3fc64b0ecbb00db92eddc1525552eda10a8656ff4b7380f66d81bda1 && \
	curl -fsSL https://developer.download.nvidia.com/compute/redist/nccl/v2.7/nccl_2.7.3-1+cuda10.2_x86_64.txz -O && \
	echo "$NCCL_DOWNLOAD_SUM nccl_2.7.3-1+cuda10.2_x86_64.txz" \| sha256sum -c - && \
	unxz nccl_2.7.3-1+cuda10.2_x86_64.txz && \
	tar --no-same-owner --keep-old-files --no-overwrite-dir -xvf nccl_2.7.3-1+cuda10.2_x86_64.tar -C /usr/local/cuda/include/ --strip-components=2 --wildcards '/include/' && \
	tar --no-same-owner --keep-old-files --no-overwrite-dir -xvf nccl_2.7.3-1+cuda10.2_x86_64.tar -C /usr/local/cuda/lib64/ --strip-components=2 --wildcards '*/lib/libnccl.so' && \
	rm -f nccl_2.7.3-1+cuda10.2_x86_64.tar && \
	ldconfig
	ENV LIBRARY_PATH /usr/local/cuda/lib64/stubs

	# 10.2-cudnn7-devel-centos7
	ENV CUDNN_VERSION 7.6.5.32
	# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
	RUN CUDNN_DOWNLOAD_SUM=600267f2caaed2fd58eb214ba669d8ea35f396a7d19b94822e6b36f9f7088c20 && \
	curl -fsSL http://developer.download.nvidia.com/compute/redist/cudnn/v7.6.5/cudnn-10.2-linux-x64-v7.6.5.32.tgz -O && \
	echo "$CUDNN_DOWNLOAD_SUM cudnn-10.2-linux-x64-v7.6.5.32.tgz" \| sha256sum -c - && \
	tar --no-same-owner -xzf cudnn-10.2-linux-x64-v7.6.5.32.tgz -C /usr/local && \
	rm cudnn-10.2-linux-x64-v7.6.5.32.tgz && \
	ldconfig

	# install nccl for distributed training
	RUN git clone https://github.com/NVIDIA/nccl.git $HOME/nccl \
	&& cd $HOME/nccl \
	&& git checkout v2.4.8-1 \
	&& make BUILDDIR=/usr/local/ -j$(nproc) src.build \
	&& rm -rf /usr/local/obj \
	&& rm -rf $HOME/nccl

	# install cnmem to /usr/local/include /usr/local/lib
	RUN git clone https://github.com/NVIDIA/cnmem.git cnmem \
	&& cd cnmem && mkdir build && cd build && cmake .. && make && make install && cd ../.. && rm -rf cnmem

	# install mpich /usr/local/include /usr/local/lib
	RUN wget http://www.mpich.org/static/downloads/3.3.2/mpich-3.3.2.tar.gz -P $HOME \
	&& cd $HOME \
	&& tar xfz mpich-3.3.2.tar.gz \
	&& cd mpich-3.3.2 \
	&& ./configure --prefix=/usr/local --disable-fortran \
	&& make && make install && cd .. && rm -rf mpich-3.3.2