Accumulation

is an element of a series about distributed AI across multiple GPUs: Introduction Distributed Data Parallelism (DDP) is the primary parallelization method we’ll have a look at. It’s the baseline approach that’s all the time utilized in...

Years of suboptimal model training?When fine-tuning large language models (LLMs) locally, using large batch sizes is commonly impractical as a consequence of their substantial GPU memory consumption. To beat this limitation, a method called...