This Machine Learning Research Presents ScatterMoE: An Implementation of Sparse Mixture-of-Experts (SMoE) on GPUs

A sparse Mixture of Experts (SMoEs) has gained traction for scaling models, especially useful in memory-constrained setups. They’re pivotal in Switch Transformer and Universal Transformers, offering efficient training and inference. However, implementing SMoEs efficiently poses challenges. Naive PyTorch implementations lack GPU parallelism, hindering performance. Also, initial deployments of TPUs need help with tensor size variability, […]

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