[CI] Build pip wheel with RMM support (#9383)

tests/ci_build/Dockerfile.gpu_build_centos7

@@ -2,6 +2,7 @@ ARG CUDA_VERSION_ARG
 FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-centos7
 ARG CUDA_VERSION_ARG
 ARG NCCL_VERSION_ARG
+ARG RAPIDS_VERSION_ARG
 
 # Install all basic requirements
 RUN \
@@ -16,8 +17,8 @@ RUN \
     bash conda.sh -b -p /opt/mambaforge && \
     /opt/mambaforge/bin/python -m pip install awscli && \
     # CMake
-    wget -nv -nc https://cmake.org/files/v3.18/cmake-3.18.0-Linux-x86_64.sh --no-check-certificate && \
-    bash cmake-3.18.0-Linux-x86_64.sh --skip-license --prefix=/usr
+    wget -nv -nc https://cmake.org/files/v3.24/cmake-3.24.0-linux-x86_64.sh --no-check-certificate && \
+    bash cmake-3.24.0-linux-x86_64.sh --skip-license --prefix=/usr
 
 # NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
 RUN \
@@ -33,9 +34,21 @@ ENV PATH=/opt/mambaforge/bin:/usr/local/ninja:$PATH
 ENV CC=/opt/rh/devtoolset-9/root/usr/bin/gcc
 ENV CXX=/opt/rh/devtoolset-9/root/usr/bin/c++
 ENV CPP=/opt/rh/devtoolset-9/root/usr/bin/cpp
+ENV CUDAHOSTCXX=/opt/rh/devtoolset-9/root/usr/bin/c++
 
 ENV GOSU_VERSION 1.10
 
+# Install RMM
+RUN git clone -b v${RAPIDS_VERSION_ARG}.00 https://github.com/rapidsai/rmm.git --recurse-submodules --depth 1 && \
+    pushd rmm && \
+    mkdir build && \
+    pushd build && \
+    cmake .. -GNinja -DCMAKE_INSTALL_PREFIX=/opt/rmm -DCUDA_STATIC_RUNTIME=ON && \
+    cmake --build . --target install && \
+    popd && \
+    popd && \
+    rm -rf rmm
+
 # Install gRPC
 RUN git clone -b v1.49.1 https://github.com/grpc/grpc.git \
       --recurse-submodules --depth 1 && \

tests/ci_build/Dockerfile.rmm

@@ -1,49 +0,0 @@
-ARG CUDA_VERSION_ARG
-FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-ubuntu20.04
-ARG CUDA_VERSION_ARG
-ARG RAPIDS_VERSION_ARG
-ARG NCCL_VERSION_ARG
-
-# Environment
-ENV DEBIAN_FRONTEND noninteractive
-SHELL ["/bin/bash", "-c"]   # Use Bash as shell
-
-# Install all basic requirements
-RUN \
-    apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub && \
-    apt-get update && \
-    apt-get install -y wget unzip bzip2 libgomp1 build-essential ninja-build git && \
-    # Python
-    wget -nv -O conda.sh https://github.com/conda-forge/miniforge/releases/download/22.11.1-2/Mambaforge-22.11.1-2-Linux-x86_64.sh && \
-    bash conda.sh -b -p /opt/mambaforge
-
-# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
-RUN \
-    export CUDA_SHORT=`echo $CUDA_VERSION_ARG | grep -o -E '[0-9]+\.[0-9]'` && \
-    export NCCL_VERSION=$NCCL_VERSION_ARG && \
-    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/mambaforge/bin:$PATH
-
-# Create new Conda environment with RMM
-RUN \
-    conda install -c conda-forge mamba && \
-    mamba create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \
-        python=3.10 rmm=$RAPIDS_VERSION_ARG* cudatoolkit=$CUDA_VERSION_ARG cmake && \
-    mamba clean --all
-
-ENV GOSU_VERSION 1.10
-
-# Install lightweight sudo (not bound to TTY)
-RUN set -ex; \
-    wget -nv -O /usr/local/bin/gosu "https://github.com/tianon/gosu/releases/download/$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"]

tests/ci_build/prune_libnccl.sh

@@ -26,7 +26,7 @@ set_property(TARGET test PROPERTY CUDA_ARCHITECTURES \${CMAKE_CUDA_ARCHITECTURES
 set(CMAKE_EXPORT_COMPILE_COMMANDS ON)
 EOF
 
-cmake . -GNinja
+cmake . -GNinja -DCMAKE_EXPORT_COMPILE_COMMANDS=ON
 gen_code=$(grep -o -- '--generate-code=\S*' compile_commands.json | paste -sd ' ')
 
 nvprune ${gen_code} /usr/lib64/libnccl_static.a -o ../libnccl_static.a