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Awesome GitHub RepositoriesDistributed Optimizer Scaling
Techniques for managing memory and synchronization of optimizer states for massive models.
Distinct from Large Model Optimizations: Focuses on distributed optimizer state management rather than general quantization or device mapping
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Awesome Distributed Optimizer Scaling GitHub Repositories
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- nvidia/apex
NVIDIA/apex
8,972在 GitHub 上查看Apex is a high-performance toolkit for PyTorch designed to coordinate distributed training, execute fused GPU kernels, manage mixed precision, and implement optimized distributed optimizers. It provides specialized tools for scaling model training across multiple GPUs and nodes to increase processing speed and throughput. The library features high-performance implementations of Adam and LAMB optimizers to reduce synchronization overhead and memory bottlenecks. It utilizes fused CUDA kernels to combine neural network operations, reducing memory overhead and increasing execution speed. The too
Manages memory overhead and synchronization for massive networks using distributed Adam and LAMB optimizers.
Python
