新闻
Large-Scale Sharded Weight Transfer with Ray Direct Transport (RDT) in vLLM
vLLM · Aaron Hao, Sumanth Hegde, Gal Meirom, Istvan Haller, Kourosh Hakhamaneshi, Gavin Parnaby, Moein Khazraee, Omri Kahalon · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- vLLM released a sharded weight transfer engine using Ray Direct Transport for efficient model synchronization in reinforcement learning, achieving 7.53 seconds for trillion-parameter models.
- 为何重要
- Matters for engineers building large-scale RL systems where periodic weight syncing between trainer and inference workers creates memory and latency bottlenecks.
- 注意
- Implementation transfers unprocessed BF16 weights after step 4 of loading pipeline, requiring inference workers to handle remaining quantization and processing steps locally.
收听本摘要
- llm
- vllm
- kimi
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