DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. DeepSpeed delivers extreme-scale model training for everyone, from data scientists training on massive supercomputers to those training on low-end clusters or even on a single GPU. Using current generation of GPU clusters with hundreds of devices, 3D parallelism of DeepSpeed can efficiently train deep learning models with trillions of parameters. With just a single GPU, ZeRO-Offload of DeepSpeed can train models with over 10B parameters, 10x bigger than the state of arts, democratizing multi-billion-parameter model training such that many deep learning scientists can explore bigger and better models. Sparse attention of DeepSpeed powers an order-of-magnitude longer input sequence and obtains up to 6x faster execution comparing with dense transformers.

Features

  • 10x larger models and 10x faster training
  • Minimal code change
  • Extremely memory efficient
  • Extremely long sequence length
  • Extremely communication efficient
  • An initiative to enable next-generation AI capabilities at scale

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License

MIT License

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Additional Project Details

Operating Systems

Windows

Programming Language

Python

Related Categories

Python Libraries, Python Machine Learning Software, Python Deep Learning Frameworks

Registered

2021-09-23