8 Commits

Author SHA1 Message Date
Jiaming Yuan
a5a58102e5
Revamp the rabit implementation. (#10112)
This PR replaces the original RABIT implementation with a new one, which has already been partially merged into XGBoost. The new one features:
- Federated learning for both CPU and GPU.
- NCCL.
- More data types.
- A unified interface for all the underlying implementations.
- Improved timeout handling for both tracker and workers.
- Exhausted tests with metrics (fixed a couple of bugs along the way).
- A reusable tracker for Python and JVM packages.
2024-05-20 11:56:23 +08:00
Jiaming Yuan
3f64b4fde3
[coll] Add global functions. (#10203) 2024-04-19 03:17:23 +08:00
Jiaming Yuan
5ac233280e
Require context in aggregators. (#10075) 2024-02-28 03:12:42 +08:00
Rong Ou
c928dd4ff5
Support vertical federated learning with gpu_hist (#9539) 2023-09-03 11:37:11 +08:00
Rong Ou
a320b402a5
More refactoring to take advantage of collective aggregators (#9081) 2023-04-26 03:36:09 +08:00
Rong Ou
8dbe0510de
More collective aggregators (#9060) 2023-04-22 03:32:05 +08:00
Jiaming Yuan
a7b3dd3176
Fix compiler warnings. (#9055) 2023-04-21 02:26:47 +08:00
Rong Ou
42d100de18
Make sure metrics work with federated learning (#9037) 2023-04-19 15:39:11 +08:00