深度神经网络加速器模拟器设计与分析综述

Mijing Sun, Li Xu, Zhenmin Li, Wei Ni, Gaoming Du, Xiaolei Wang, Yong-Sheng Yin
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引用次数: 0

摘要

随着机器学习技术,尤其是深度学习技术的快速发展,人们对深度神经网络(DNN)加速器等特定领域处理器的研究关注度急剧增加。深度神经网络加速器的规模和复杂性的激增带来了巨大的设计挑战。具有高仿真速度和准确性能评估能力的仿真器是深度神经网络加速器设计的关键。一些针对深度神经网络加速器的模拟器已经出现,但它们并没有被总结和分类。本文从仿真器性能、目标平台、评估指标、输入/输出特性和实现细节等方面对目前最先进的深度神经网络加速器仿真器进行了系统综述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulators for Deep Neural Network Accelerator Design and Analysis: A Brief Review
The rapid development of machine learning techniques, especially deep learning, has led to a drastic increase of research attention for domain-specific processors such as deep neural networks (DNN) accelerators. The surge in scale and complexity of DNN accelerators poses great design challenge. Simulators with high simulation speed and accurate performance evaluation capability are pivotal for DNN accelerator design. A number of simulators targeting DNN accelerators have emerged, yet they are not summarized and classified. This paper presents a systematic review of state-of-the-art DNN accelerator simulator from the perspective of simulator performance, target platform, evaluation indicators, input/output characteristics, and implementation details.
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