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wskwon

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vLLM: Easy, Fast, and Cheap LLM Serving with PagedAttention

vllm.ai
295 points·by wskwon·قبل 3 سنوات·42 comments

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wskwon
·قبل 3 سنوات·discuss
Thanks! Please try it out and share any feedback you might have.
wskwon
·قبل 3 سنوات·discuss
Thanks for the explanation! I believe the two ideas are basically orthogonal. FlashAttention reduces memory read/writes, while PagedAttention reduces memory waste.
wskwon
·قبل 3 سنوات·discuss
Yes, vLLM focuses on maximizing throughput when the VRAM is fully utilized. Nevertheless, I believe users can still benefit from vLLM even if they don't utilize the memory to its full capacity, because vLLM also includes other optimizations orthogonal to the PagedAttention (e.g., optimized CUDA kernels).
wskwon
·قبل 3 سنوات·discuss
We used matplotlib for the performance charts, and used a free website to convert google slides to the animation gifs.
wskwon
·قبل 3 سنوات·discuss
Not really. vLLM optimizes the throughput of your LLM, but does not reduce the minimum required amount of resource to run your model.
wskwon
·قبل 3 سنوات·discuss
You can think of LMSYS Vicuna: https://chat.lmsys.org as our hosted demo, as it actually uses vLLM as the backend.
wskwon
·قبل 3 سنوات·discuss
vLLM has been adopted by LMSYS for serving Vicuna and Chatbot Arena.