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Yuan, Zhe, et al. “14.2 A 65nm 24.7 µJ/Frame 12.3 mW Activation-Similarity-Aware Convolutional Neural Network Video Processor Using Hybrid Precision, Inter-Frame Data Reuse and Mixed-Bit-Width Difference-Frame Data Codec.” 2020 IEEE International Solid-Sta

Liu, Shaoli, et al. “Cambricon: an instruction set architecture for neural networks.” international symposium on computer architecture (2016): 393-405.Zhang, Shijin, et al. “Cambricon-x: an accelerator for sparse neural networks.” international symposium

Semiconductor System Lab. School of EE, KAIST韩国科学技术院（Korea Advanced Institute of Science and Technology,KAIST)Kang, Sanghoon, et al. “7.4 GANPU: A 135TFLOPS/W Multi-DNN Training Processor for GANs with Speculative Dual-Sparsity Exploitation.” 2020 IEEE I

本文汇总了近年来关于Deep-Learning Processor领域的相关论文。2014ASPLOSChen, Tianshi, et al. “DianNao: a small-footprint high-throughput accelerator for ubiquitous machine-learning.” architectural support for programming languages and operating systems (2014): 269-284.MIC

01前言人工智能领域中，由于深度学习的技术（Deep Learning）在图像识别，语音识别，自动驾驶等应用取得了非常不错的效果。深度学习中，例如：卷积神经网络（CNN），深度网络（DNN），递归神经网络（RNN），它们具有参数量多，计算量大，并行度高的特征。传统采用GPU，CPU的处理方式并不适用于该计算特征，故设计一种面向深度学习领域的专用处理器（Deep-Learning Processor）是非常必要的。本文从JSSC 2016 ：Eyeriss 一篇论文谈起。02...