Techniques for training large neural networks

OpenAI Blog · 4 years ago

Training large neural networks requires coordinating multiple GPUs across a cluster to perform synchronized calculations. The practical engineering challenge involves managing communication and computation across distributed hardware without bottlenecks. Organizations now use specialized techniques like gradient accumulation, mixed precision training, and distributed data parallelism to make large-scale training feasible.