* Update to C++17
* Turn off unity build
* Update CMake to 3.18
* Use MSVC 2022 + CUDA 11.8
* Re-create stack for worker images
* Allocate more disk space for Windows
* Tempiorarily disable clang-tidy
* RAPIDS now requires Python 3.10+
* Unpin cuda-python
* Use latest NCCL
* Use Ubuntu 20.04 in RMM image
* Mark failing mgpu test as xfail
* [CI] Use Vault repository to re-gain access to devtoolset-4
* Use manylinux2010 tag
* Update Dockerfile.jvm
* Fix rename_whl.py
* Upgrade Pip, to handle manylinux2010 tag
* Update insert_vcomp140.py
* Update test_python.sh
* Add inplace prediction for dask-cudf.
* Remove Dockerfile.release, since it's not used anywhere
* Use Conda exclusively in CUDF and GPU containers
* Improve cupy memory copying.
* Add skip marks to tests.
* Add mgpu-cudf category on the CI to run all distributed tests.
Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
* Ensure that configured header (build_config.h) from dmlc-core is picked up by Rabit and XGBoost
* Check which Rabit target is being used
* Use CMake 3.13 in all Jenkins tests
* Upgrade CMake in Travis CI
* Install CMake using Kitware installer
* Remove existing CMake (3.12.4)
* Use devtoolset-6.
* [CI] Use devtoolset-6 because devtoolset-4 is EOL and no longer available
* CUDA 9.0 doesn't work with devtoolset-6; use devtoolset-4 for GPU build only
Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
* All Linux tests are now in Jenkins CI
* Tests are now de-coupled from builds. We can now build XGBoost with one version of CUDA/JDK and test it with another version of CUDA/JDK
* Builds (compilation) are significantly faster because 1) They use C5 instances with faster CPU cores; and 2) build environment setup is cached using Docker containers
