
Official account for DeepSpeed, a library that enables unprecedented scale and speed for deep learning training + inference. 日本語 : @DeepSpeedAI_JP
Joined May 2020
- Tweets122
- Following93
- Followers4.2K
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Improved DeepNVMe: Affordable I/O Scaling for AI
- Faster I/O with PCIe Gen5
- 20x faster model checkpointing
- Low-budget SGLang inference via NVMe offloading
- Pinned memory for CPU-only workloads
- Zero-copy tensor type casting
Blog: tinyurl.com/yanbrjy9
Introducing 🚀DeepCompile🚀: compiler-based distributed training optimizations.
- Automatic parallelization & profile-guided optimizations
- Enable ZeRO1, ZeRO3, Offloading, etc. via compiler passes
- 1.2X-7X speedups over manual ZeRO1/ZeRO3/Offloading
tinyurl.com/8cys28xk
AutoTP + ZeRO Training for HF Models
- Enhance HF post-training with larger models, batches, & contexts
- 4x faster LLAMA3 fine-tuning with TP=2 vs TP=1
- No code changes needed
Blog: tinyurl.com/5n8nfs2w
🚀Introducing Ulysses-Offload🚀
- Unlock the power of long context LLM training and finetuning with our latest system optimizations
- Train LLaMA3-8B on 2M tokens context using 4xA100-80GB
- Achieve over 55% MFU
Blog: shorturl.at/Spx6Y
Tutorial: shorturl.at/bAWu5
Introducing Domino: a novel zero-cost communication tensor parallelism (TP) training engine for both single node and multi-node settings.
- Near-complete communication hiding
- Novel multi-node scalable TP solution
Blog: github.com/microsoft/DeepSpe…
Announcing that DeepSpeed now runs natively on Windows. This exciting combination unlocks DeepSpeed optimizations to Windows users and empowers more people and organizations with AI innovations.
- HF Inference & Finetuning
- LoRA
- CPU Offload
Blog: shorturl.at/a7TF8
Introducing DeepNVMe, a suite of optimizations for fast and efficient I/O operations in DL applications.
- POSIX-style APIs
- Direct HBM/NVMe xfers via NVIDIA GDS
- Cheap Inference scaling via NVMe-Offload
Blog: shorturl.at/l7Oue
@Azure
@NVIDIADC
#FMS24
#GPUDirect
Introducing Universal Checkpointing for boosting training efficiency.
- Change parallelism (PP, SP, TP, ZeRO-DP) or GPU count mid-stream
- Improve resilience by scaling down to healthy nodes💪
- Increase throughput by scaling up to elastic nodes🚀
Blog: rb.gy/aup3pn
#DeepSpeed joins forces with @Sydney_Uni to unveil an exciting tech #FP6. Just supply your FP16 models, and we deliver:
🚀 1.5x performance boost for #LLMs serving on #GPUs
🚀 Innovative (4+2)-bit system design
🚀 Quality-preserving quantization
link: github.com/microsoft/DeepSpe…
Introducing Mixtral, Phi2, Falcon, and Qwen support in #DeepSpeed-FastGen!
- Up to 2.5x faster LLM inference
- Optimized SplitFuse and token sampling
- Exciting new features like RESTful API and more!
For more details: github.com/microsoft/DeepSpe…
#DeepSpeeed #AI











