JSSC 2021第1期Clocking & PLLs65nmNeural Network Accelerator

A Dynamic Timing Enhanced DNN Accelerator With Compute-Adaptive Elastic Clock Ch

提出一种基于弹性时钟链的动态时序增强DNN加速器，通过多域时钟管理提升性能与能效

6×8 PE阵列，MNIST和CIFAR-10数据集上运行频率提升19%，能耗降低34%

DNN加速器弹性时钟链动态时序裕量多域时钟管理能效优化

▸弹性时钟链技术实现动态时序裕量利用

▸16个时钟域的多域时钟管理方案

▸基于运行时指令和操作数的动态时钟周期调整

Abstract

This article presents a deep neural network (DNN) accelerator using an adaptive clocking technique (i.e., elastic clock chain) to exploit the dynamic timing margin for the 2-D processing element (PE) array-based DNN accelerator. To address two major challenges on exploiting dynamic timing margin for modern deep learning accelerators (i.e., diminishing dynamic timing margin on a large array and strong timing dependence on runtime operands), in this work, we proposed an elastic clock chain scheme