[HPEC2024] GLITCHES: GPU-FPGA LLM Inference Through a Collaborative Heterogeneou, 视频播放量 221、弹幕量 0、点赞数 5、投硬币枚数 4、收藏人数 6、转发人数 5, 视频作者 清华大学NICS-EFC实验室, 作者简介 不定期更新! 清华大学NICS-EFC实验室 https://nicsefc.ee.ts
Batch inference speedup of Falcon-40B on PC-High. The X axis indicates the request batch size, the Y axis represents the end-to-end token generation speed (tokens/s). The number above each bar shows the speedup compared with 负载对比 Neuron load distribution on CPU and GPU during inference...
如果和decode阶段比较,prefill无论计算多少token的用户输入都是一次模型的inference,权重和更前面的KV理论上只要访问一次就可以,但计算量随着用户输入token长度增加成正比增加,绝大多数情况是算力bound。而decode阶段因为每个token都需要对模型进行一次inference,并对权重和KV进行一次访问,总的访存量和用户输入token数成正比,...
A technical paper titled “Efficient LLM Inference on CPUs” was published by researchers at Intel. Abstract: “Large language models (LLMs) have demonstrated remarkable performance and tremendous potential across a wide range of tasks. However, deploying these models has been challenging due to the...
如果和decode阶段比较,prefill无论计算多少token的用户输入都是一次模型的inference,权重和更前面的KV理论上只要访问一次就可以,但计算量随着用户输入token长度增加成正比增加,绝大多数情况是算力bound。而decode阶段因为每个token都需要对模型进行一次inference,并对权重和KV进行一次访问,总的访存量和用户输入token数成正比,...
如果和decode阶段比较,prefill无论计算多少token的用户输入都是一次模型的inference,权重和更前面的KV理论上只要访问一次就可以,但计算量随着用户输入token长度增加成正比增加,绝大多数情况是算力bound。而decode阶段因为每个token都需要对模型进行一次inference,并对权重和KV进行一次访问,总的访存量和用户输入token数成正比,...
人的学习其实对应的不是深度学习的训练过程,而是inference的一个小步骤,人的一辈子就是一次inference过程,获取输入,提取经验,再接受新的输入,并根据之前提取的经验快速得到结论。“经验”其实就类似于attention机制中的权重,inference过程中动态生成,并用于给其他数据进行加权,而神经图灵机将经验存储起来。
📖CPU/Single GPU/FPGA/Mobile Inference (©️back👆🏻)DateTitlePaperCodeRecom 2023.03 [FlexGen] High-Throughput Generative Inference of Large Language Models with a Single GPU(@Stanford University etc) [pdf] [FlexGen] ⭐️ 2023.11 [LLM CPU Inference] Efficient LLM Inference on CPUs(@...
2024-12-15 NITRO: LLM Inference on Intel Laptop NPUs Anthony Fei et.al. 2412.11053 link 2024-12-13 SCBench: A KV Cache-Centric Analysis of Long-Context Methods Yucheng Li et.al. 2412.10319 null 2024-12-17 TurboAttention: Efficient Attention Approximation For High Throughputs LLMs Hao Kang...
RaiderChip launches its Generative AI hardware accelerator for LLM models on low-cost FPGAsThe startup pioneers Edge Generative AI inference on small devices, thanks to the efficiency of its AI accelerator IP core: the GenAI v1 Spain, June 4th, 2024 -- The company, which recently annou...