0ee11dac77
Following classes are added to support dataframe in java binding: - `Column` is an abstract type for a single column in tabular data. - `ColumnBatch` is an abstract type for dataframe. - `CuDFColumn` is an implementaiton of `Column` that consume cuDF column - `CudfColumnBatch` is an implementation of `ColumnBatch` that consumes cuDF dataframe. - `DeviceQuantileDMatrix` is the interface for quantized data. The Java implementation mimics the Python interface and uses `__cuda_array_interface__` protocol for memory indexing. One difference is on JVM package, the data batch is staged on the host as java iterators cannot be reset. Co-authored-by: jiamingy <jm.yuan@outlook.com>
55 lines
2.4 KiB
Docker
55 lines
2.4 KiB
Docker
ARG CUDA_VERSION_ARG
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FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-centos7
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ARG CUDA_VERSION_ARG
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# Install all basic requirements
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RUN \
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yum install -y epel-release centos-release-scl && \
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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 tar unzip wget xz git which ninja-build java-1.8.0-openjdk-devel devtoolset-8-gcc devtoolset-8-binutils devtoolset-8-gcc-c++ && \
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# Python
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wget -nv -nc -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/v3.14/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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# Maven
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wget -nv -nc 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 $CUDA_VERSION_ARG | grep -o -E '[0-9]+\.[0-9]'` && \
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export NCCL_VERSION=2.8.3-1 && \
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wget -nv -nc https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
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rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
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yum -y update && \
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yum install -y libnccl-${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-8/root/usr/bin/gcc
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ENV CXX=/opt/rh/devtoolset-8/root/usr/bin/c++
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ENV CPP=/opt/rh/devtoolset-8/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 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 -nv -nc -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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