Spatial Data Dependence Graph Simulator for Convolutional Neural Network Accelerators

Jooho Wang, Ji-Won Kim, Sungmin Moon, Sunwoo Kim, Sungkyung Park, C. Park
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引用次数: 2

Abstract

A spatial data dependence graph (S-DDG) is newly proposed to model an accelerator dataflow. The pre-RTL simulator based on the S-DDG helps to explore the design space in the early design phase. The simulation results show the impact of memory latency and bandwidth on a convolutional neural network (CNN) accelerator.
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卷积神经网络加速器的空间数据依赖图模拟器
提出了一种空间数据依赖图(S-DDG)来对加速器数据流进行建模。基于S-DDG的预rtl模拟器有助于在早期设计阶段探索设计空间。仿真结果显示了存储延迟和带宽对卷积神经网络加速器的影响。
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