MEGA.mini: A Universal Generative AI Processor with a New Big/Little Core Architecture for NPU

📋 论文概要

论文提出了一种名为MEGA.mini的通用生成式AI处理器，采用新的大/小核架构用于NPU，旨在高效处理图像编辑、文本生成等生成式AI任务。解决了传统NPU在处理多样化的生成式DNN模型时灵活性和效率不足的问题。

💡 主要创新点

• 提出大/小核异构架构，大核处理高算力需求任务，小核处理轻量级任务，实现能效与性能的平衡。
• 设计通用生成式AI处理器，支持多种DNN模型（如文本到图像、视频生成等），具备可编程性和可扩展性。

🏷 关键词

📄 原文摘要

Chung-Ang University, Seoul, Korea 1 2 The global AI market is growing explosively with the rise of generative AI applications, such as image manipulation and text-to-text/image/video creation. AI was primarily expected to automate only simple tasks like classification and data analysis. However, the advent of generative AI has transformed it into a creativity assistant, helping people think more creatively by offering new perspectives through deep neural networks (DNNs). As shown in Fig. 23.6.1, there are various types of DNNs used in generative AI, which can be categorized into two groups: non-diffusion models (NDMs) and diffusion models (DMs). NDMs, such as variational autoencoders (VAEs), generative adversarial networks (GANs), and transformers, are still predominantly used. DMs require 25-100× more operations due to their need for iterative inference (INF). Consequently, generative AI processors need to

👥 作者与机构

Donghyeon Han1,2, Anantha P. Chandrakasan1

Massachusetts Institute of Technology, Cambridge, MA