* Fix test_gpu_coordinate.
* Use `gpu_coord_descent` in test.
* Reduce number of running rounds.
* Remove nthread.
* Use githubusercontent for r-appveyor.
* Use githubusercontent in travis r tests.
* Add multi-GPU unit test environment
* Better assertion message
* Temporarily disable failing test
* Distinguish between multi-GPU and single-GPU CPP tests
* Consolidate Python tests. Use attributes to distinguish multi-GPU Python tests from single-CPU counterparts
* Fix#3730: scikit-learn 0.20 compatibility fix
sklearn.cross_validation has been removed from scikit-learn 0.20,
so replace it with sklearn.model_selection
* Display test names for Python tests for clarity
* Added finding quantiles on GPU.
- this includes datasets where weights are assigned to data rows
- as the quantiles found by the new algorithm are not the same
as those found by the old one, test thresholds in
tests/python-gpu/test_gpu_updaters.py have been adjusted.
* Adjustments and improved testing for finding quantiles on the GPU.
- added C++ tests for the DeviceSketch() function
- reduced one of the thresholds in test_gpu_updaters.py
- adjusted the cuts found by the find_cuts_k kernel
* Fail GPU CI after test failure
* Fix GPU linear tests
* Reduced number of GPU tests to speed up CI
* Remove static allocations of device memory
* Resolve illegal memory access for updater_fast_hist.cc
* Fix broken r tests dependency
* Update python install documentation for GPU
* Fix#2905
* Fix gpu_exact test failures
* Fix bug in GPU prediction where multiple calls to batch prediction can produce incorrect results
* Fix GPU documentation formatting
- Implement colsampling, subsampling for gpu_hist_experimental
- Optimised multi-GPU implementation for gpu_hist_experimental
- Make nccl optional
- Add Volta architecture flag
- Optimise RegLossObj
- Add timing utilities for debug verbose mode
- Bump required cuda version to 8.0
