Flash-Decoding for Long-Context Inference 1. Flash-Decoding的基本概念 Flash-Decoding是一种用于加速长序列推理过程中注意力机制(Attention Mechanism)计算的技术。它是在FlashAttention的基础上发展而来的,通过增加对键(Keys)和值(Values)序列长度的并行化,
Flash Decoding(FD)是FlashAttention(FA)针对推理场景的改进版本,它的设计思想在2023.10.13发布在如下PyTorch官方blog。如果大家了解FA原理的话会觉得FD改进非常自然。 Flash-Decoding for long-context inference 关于FlashAttention V1和V2如何加速LLM训练的技术,可以看我之前的文章: 方佳瑞:大模型训练加速之FlashAttentio...
We present a technique, Flash-Decoding, that significantly speeds up attention during inference, bringing up to 8x faster generation for very long sequences. The main idea is to load the keys and values in parallel as fast as possible, then separately rescale and combine the results to maintain...
Flash-Decoding for long-context inference Authors: Tri Dao and Daniel Haziza and Francisco Massa and Grigory Sizov原论文 Stanford CRFM动机 最近,像ChatGPT或Llama这样的大型语言模型(LLM)引起了前所未…
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-related:[Flash-Decoding for long-context inference](https://www.together.ai/blog/flash-decoding-for-long-context-inference)(together.ai blog) 2323 2424 -Paper:[Online normalizer calculation for softmax](https://arxiv.org/abs/1805.02867)(NVIDIA, 2018) ...
As the Large Language Model (LLM) achieved unprecedented success in various domains [2, 3, 4, 5], the LLM inference workload is skyrocketing. For example, OpenAI reports that GPT-4 inference with 8K context length costs $0.03 per 1K input tokens and $0.06 per 1K output tokens [6]. ...
上图为Flash-Decoding for long-context inference中对Flash-decoding动画展示,FA-2issue中对Flash-decoding也进行了讨论,对应falsh-decoding代码片段在:https://github.com/Dao-AILab/flash-attention/blob/53a4f341634fcbc96bb999a3c804c192ea14f2ea/csrc/flash_attn/src/flash_fwd_kernel.h#L1108,FA-2论 文...
In this setting (long context inference), attention takes a significant fraction of time during inference. The main idea (of Flash Decoding, aka. FlashAttention-V3) is to load the keys and values in parallel as fast as possible, then separately rescale and combine the results to maintain the...
Need O(n^2) Memoryhttps://arxiv.org/abs/2112.05682^Flash-Decoding for long-context inference....