deepspeed

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Expert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attention

AI & Automation 9,609 stars 724 forks Updated 1 months ago MIT

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Skill Content

# Deepspeed Skill Comprehensive assistance with deepspeed development, generated from official documentation. ## When to Use This Skill This skill should be triggered when: - Working with deepspeed - Asking about deepspeed features or APIs - Implementing deepspeed solutions - Debugging deepspeed code - Learning deepspeed best practices ## Quick Reference ### Common Patterns **Pattern 1:** DeepNVMe Contents Requirements Creating DeepNVMe Handles Using DeepNVMe Handles Blocking File Write Non-Blocking File Write Parallel File Write Pinned Tensors Putting it together Acknowledgements Appendix Advanced Handle Creation Performance Tuning DeepNVMe APIs General I/O APIs GDS-specific APIs Handle Settings APIs This tutorial will show how to use DeepNVMe for data transfers between persistent storage and tensors residing in host or device memory. DeepNVMe improves the performance and efficiency of I/O operations in Deep Learning applications through powerful optimizations built on Non-Volatile Memory Express (NVMe) Solid State Drives (SSDs), Linux Asynchronous I/O (libaio), and NVIDIA Magnum IOTM GPUDirect® Storage (GDS). Requirements Ensure your environment is properly configured to use DeepNVMe. First, you need to install DeepSpeed version >= 0.15.0. Next, ensure that the DeepNVMe operators are available in the DeepSpeed installation. The async_io operator is required for any DeepNVMe functionality, while the gds operator is required only for GDS functionality. You can confirm a...

Details

Author
Orchestra-Research
Repository
Orchestra-Research/AI-Research-SKILLs
Created
7 months ago
Last Updated
1 months ago
Language
TeX
License
MIT

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