Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Add GPU support to NVFlare demo (#9552)

Browse Source
This commit is contained in:
Rong Ou
2023-09-06 02:03:59 -07:00
committed by GitHub
parent 3b9e5909fb
commit 0f35493b65
4 changed files with 14 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
demo/nvflare/horizontal/README.md
View File

@@ -85,8 +85,8 @@ shutdown server
## Training with GPUs
To demo with Federated Learning using GPUs, make sure your machine has at least 2 GPUs.
Build XGBoost with the federated learning plugin enabled along with CUDA, but with NCCL
turned off (see the [README](../../plugin/federated/README.md)).
Build XGBoost with the federated learning plugin enabled along with CUDA
(see the [README](../../plugin/federated/README.md)).
Modify `config/config_fed_client.json` and set `use_gpus` to `true`, then repeat the steps
Modify `../config/config_fed_client.json` and set `use_gpus` to `true`, then repeat the steps
above.

2
demo/nvflare/horizontal/custom/trainer.py
View File

@@ -67,7 +67,7 @@ class XGBoostTrainer(Executor):
dtest = xgb.DMatrix('agaricus.txt.test?format=libsvm')
# Specify parameters via map, definition are same as c++ version
param = {'max_depth': 2, 'eta': 1, 'objective': 'binary:logistic'}
param = {'tree_method': 'hist', 'max_depth': 2, 'eta': 1, 'objective': 'binary:logistic'}
if self._use_gpus:
self.log_info(fl_ctx, f'Training with GPU {rank}')
param['device'] = f"cuda:{rank}"