Darwin: A neuromorphic hardware co-processor based on spiking neural networks
Darwin: A neuromorphic hardware co-processor based on spiking neural networks
复制标题
Darwin：基于尖峰神经网络的神经形态硬件协处理器
DOI：
10.1016/j.sysarc.2017.01.003
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发表时间：
2017-06-01
影响因子：
4.5
通讯作者：
Pan, Gang
中科院分区：
文献类型：
--
作者：
Ma, De;Shen, Juncheng;Pan, Gang
尖峰神经网络（Spiking Neural Network，SNN）是一种基于离散尖峰信号进行信息处理的生物神经网络，不同于传统的人工神经网络。SNN的硬件实现是实现高性能和低功耗的必要条件。我们提出了达尔文神经处理单元（NPU），一个高度可配置的神经形态硬件协处理器的基础上SNN实现的数字逻辑，支持可配置数量的神经元，突触和突触延迟。达尔文NPU采用标准180 nm CMOS技术制造，面积尺寸为5 x 5 mm（2），最差情况下的时钟频率为70 MHz。在典型应用中，采用1.8 V电源供电时，功耗为0.84 mW/MHz。两个原型应用程序被用来证明性能和效率的达尔文NPU。(C)2017爱思唯尔B. V.保留所有权利。
Spiking Neural Network (SNN) is a type of biologically-inspired neural networks that perform information processing based on discrete-time spikes, different from traditional Artificial Neural Network (ANN). Hardware implementation of SNNs is necessary for achieving high-performance and low-power. We present the Darwin Neural Processing Unit (NPU), a highly-configurable neuromorphic hardware co-processor based on SNN implemented with digital logic, supporting a configurable number of neurons, synapses and synaptic delays. The Darwin NPU was fabricated by standard 180 nm CMOS technology with area size of 5 x 5 mm(2) and 70 MHz clock frequency at the worst case. It consumes 0.84 mW/MHz with 1.8 V power supply for typical applications. Two prototype applications are used to demonstrate the performance and efficiency of the Darwin NPU. (C) 2017 Elsevier B.V. All rights reserved.