[Feature Proposal] Distributed Training for FL
slyviacassell opened this issue · 3 comments
slyviacassell commented
As the title described, does standalone mode support multiple GPUs to speed up training?
dunzeng commented
We didn't provide multiple GPUs in the standalone module.
However, you can use the DP module of PyTorch in train
function in SGDSerialClientTrainer.
slyviacassell commented
We define the following variables to further illustrate the idea:
- K: the number of clients who participated in training each round
- N: the number of available GPUs
When K == N, each selected client is allocated to a GPU to train.
When K > N, multiple clients are allocated to a GPU, then they execute training sequentially in the GPU.
When K < N, you can adjust to use fewer GPUs in training.
We need to set the number of GPUs in gpu
and specific distributed settings in the distributed
configs.
The implementation is under working. Anybody would like to help?