Distributed Training, Model Parallelism, Data Parallelism, Pytorch, Aurorain.
parallelism, replicating the same model for all training cores. PyTorch alleviates the parallel implementation and wraps it with minimal changes. In a nutshell, you need to specify neural network layers and immediate outputs to the desired cores via “to(device)” in three corresponding areas: