这些改进使得在使用相同speculative model的情况下,相比vLLM V0实现了高达1.42倍的端到端加速,即使在高度优化的vLLM基线之上,也能达到理论推测解码加速的91%。 结合Suffix Decoding和MLP/LSTM-Speculator 在实际的LLM部署中,往往需要同时处理重复和非重复的生成。利用后缀解码现有的评分函数,可以
vllm--speculative decoding 背景 LLM大多是纯Decode-Only架构的,在推理过程中是一个一个token预测的,哪怕是用上了KV-Cache。 Speculative Decoding需要准备两个模型:一个是大模型(Target model), 一个是小模型(Draft Model) 大模型逐个token生成太耗时,每一轮都要做数据访存 小模型输出分布接近大模型,可以通过蒸...
[Cuda mode] Lecture 22:Speculative Decoding in VLLM, 视频播放量 201、弹幕量 0、点赞数 5、投硬币枚数 0、收藏人数 11、转发人数 1, 视频作者 竹言见智, 作者简介 gzh:竹言见智,相关视频:Ray Summit 2024,The State of vLLM,[Cuda mode] Lecture 28: Liger Kerne
推测解码(Speculative Decoding),作为2023年新兴的一项LLM推理加速技术,正是提出了一种类似的解决方案:通过增加每个解码步LLM计算的并行性,减少总的解码步数(即减少了LLM参数的反复读写),从而实现推理加速。 如上右图所示,在每个解码步,推测解码首先高效地“推测”target LLM(待加速的LLM)未来多个解码步可能生成的token...
Today, AWS announces the release of Neuron 2.18, introducing stable support (out of beta) for PyTorch 2.1, adding continuous batching with vLLM support, and adding support for speculative decoding with Llama-2-70B sample in Transformers NeuronX library....
Speculative decoding involves predicting a sequence of future tokens, referred to as draft tokens, using a method that is substantially more efficient than repeatedly executing the target Large Language Model (LLM). These draft tokens are then collectively validated by processing them thr...
Proposal to improve performance Hello Teacher, it is a great honor to witness your magnificent work. The team I am part of is currently trying to migrate the inference service from TGI to vLLM. However, we have encountered some issues in...
github repo: https://github.com/dilab-zju/self-speculative-decoding Using partial layers for guess, and achive about 1.78x speed up. No draft model, the only thing needed to be cared is kv cache. Seems supports samping decoding. Cause th...
We explore the challenges presented by the LLM encoding and decoding (aka generation) and how these interact with various hardware constraints such as FLOPS, memory footprint and memory bandwidth to limit key inference metrics such as time-to-first-token, tokens per second, and tokens per joule...
NVIDIA TensorRT-LLM support for speculative decoding now provides over 3x the speedup in total token throughput. TensorRT-LLM is an open-source library that…