“In the field of large-scale deep learning, a novel algorithm has been proposed to generate optimal parallelism strategies with minimal memory redundancy. Expert researchers have formulated the parallelism strategy search problem into an integer linear programming problem and used an efficient solver to find minimal-memory intra-operator parallelism strategies. This approach achieves memory savings of up to 67% compared to the latest Megatron-LM strategies.”