Distributed Training, Model Parallelism, Data Parallelism, Pytorch, Aurorain.
is fixed, but larger weight matrices will apply more computation to each token. The second row demonstrates how the data batch is split across cores. Each core holds the same number of tokens, maintaining a fixed memory usage across all strategies. The partitioning strategies have different