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HammingMesh: A Network Topology for Large-Scale Deep Learning
Numerous microarchitectural optimizations unlocked tremendous processing power for deep neural networks that in turn fueled the AI revolution.
Breaking (Global) Barriers in Parallel Stochastic Optimization with Wait-Avoiding Group Averaging
For evaluation, we train ResNet-50 on ImageNet; Transformer for machine translation; and deep reinforcement learning for navigation at scale.
Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations
Load imbalance pervasively exists in distributed deep learning training systems, either caused by the inherent imbalance in learned tasks or by the system itself.
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