This makes GPU Hist robust in distributed environment as some workers might not be associated with any data in either training or evaluation. * Disable rabit mock test for now: See #5012 . * Disable dask-cudf test at prediction for now: See #5003 * Launch dask job for all workers despite they might not have any data. * Check 0 rows in elementwise evaluation metrics. Using AUC and AUC-PR still throws an error. See #4663 for a robust fix. * Add tests for edge cases. * Add `LaunchKernel` wrapper handling zero sized grid. * Move some parts of allreducer into a cu file. * Don't validate feature names when the booster is empty. * Sync number of columns in DMatrix. As num_feature is required to be the same across all workers in data split mode. * Filtering in dask interface now by default syncs all booster that's not empty, instead of using rank 0. * Fix Jenkins' GPU tests. * Install dask-cuda from source in Jenkins' test. Now all tests are actually running. * Restore GPU Hist tree synchronization test. * Check UUID of running devices. The check is only performed on CUDA version >= 10.x, as 9.x doesn't have UUID field. * Fix CMake policy and project variables. Use xgboost_SOURCE_DIR uniformly, add policy for CMake >= 3.13. * Fix copying data to CPU * Fix race condition in cpu predictor. * Fix duplicated DMatrix construction. * Don't download extra nccl in CI script.
24 lines
516 B
CMake
24 lines
516 B
CMake
if (NVML_LIBRARY)
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unset(NVML_LIBRARY CACHE)
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endif(NVML_LIBRARY)
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set(NVML_LIB_NAME nvml)
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find_path(NVML_INCLUDE_DIR
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NAMES nvml.h
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PATHS ${CUDA_HOME}/include ${CUDA_INCLUDE} /usr/local/cuda/include)
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find_library(NVML_LIBRARY
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NAMES nvidia-ml)
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message(STATUS "Using nvml library: ${NVML_LIBRARY}")
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include(FindPackageHandleStandardArgs)
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find_package_handle_standard_args(NVML DEFAULT_MSG
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NVML_INCLUDE_DIR NVML_LIBRARY)
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mark_as_advanced(
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NVML_INCLUDE_DIR
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NVML_LIBRARY
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)
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