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[Breaking] Upgrade cuDF and RMM to 0.18 nightlies; require RMM 0.18+ for RMM plugin (#6510)

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* [CI] Upgrade cuDF and RMM to 0.18 nightlies

* Modify RMM plugin to be compatible with RMM 0.18

* Update src/common/device_helpers.cuh

Co-authored-by: Mark Harris <mharris@nvidia.com>

Co-authored-by: Mark Harris <mharris@nvidia.com>
This commit is contained in:
Philip Hyunsu Cho 2020-12-16 10:07:52 -08:00 committed by GitHub
parent d8d684538c
commit bf6cfe3b99
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3 changed files with 3 additions and 3 deletions
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2
src/common/device_helpers.cuh
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@ -429,7 +429,7 @@ struct XGBDefaultDeviceAllocatorImpl : XGBBaseDeviceAllocator<T> {
} }
#if defined(XGBOOST_USE_RMM) && XGBOOST_USE_RMM == 1 #if defined(XGBOOST_USE_RMM) && XGBOOST_USE_RMM == 1
XGBDefaultDeviceAllocatorImpl() XGBDefaultDeviceAllocatorImpl()
: SuperT(rmm::mr::get_current_device_resource(), cudaStream_t{nullptr}) {} : SuperT(rmm::cuda_stream_default, rmm::mr::get_current_device_resource()) {}
#endif // defined(XGBOOST_USE_RMM) && XGBOOST_USE_RMM == 1 #endif // defined(XGBOOST_USE_RMM) && XGBOOST_USE_RMM == 1
}; };

2
tests/ci_build/Dockerfile.gpu
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@ -19,7 +19,7 @@ ENV PATH=/opt/python/bin:$PATH
# Create new Conda environment with cuDF, Dask, and cuPy # Create new Conda environment with cuDF, Dask, and cuPy
RUN \ RUN \
conda create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \ conda create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \
python=3.7 cudf=0.17* rmm=0.17* cudatoolkit=$CUDA_VERSION_ARG dask dask-cuda dask-cudf cupy \ python=3.7 cudf=0.18* rmm=0.18* cudatoolkit=$CUDA_VERSION_ARG dask dask-cuda dask-cudf cupy \
numpy pytest scipy scikit-learn pandas matplotlib wheel python-kubernetes urllib3 graphviz hypothesis numpy pytest scipy scikit-learn pandas matplotlib wheel python-kubernetes urllib3 graphviz hypothesis
ENV GOSU_VERSION 1.10 ENV GOSU_VERSION 1.10

2
tests/ci_build/Dockerfile.rmm
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@ -29,7 +29,7 @@ ENV PATH=/opt/python/bin:$PATH
# Create new Conda environment with RMM # Create new Conda environment with RMM
RUN \ RUN \
conda create -n gpu_test -c nvidia -c rapidsai-nightly -c rapidsai -c conda-forge -c defaults \ conda create -n gpu_test -c nvidia -c rapidsai-nightly -c rapidsai -c conda-forge -c defaults \
python=3.7 rmm=0.17* cudatoolkit=$CUDA_VERSION_ARG python=3.7 rmm=0.18* cudatoolkit=$CUDA_VERSION_ARG
ENV GOSU_VERSION 1.10 ENV GOSU_VERSION 1.10