中国科学院计算技术研究所机构知识库

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发表日期：2019

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	SqueezeFlow: A Sparse CNN Accelerator Exploiting Concise Convolution Rules 期刊论文 IEEE TRANSACTIONS ON COMPUTERS, 2019, 卷号: 68, 期号: 11, 页码: 1663-1677 作者:  Li, Jiajun;  Jiang, Shuhao;  Gong, Shijun;  Wu, Jingya;  Yan, Junchao;  Yan, Guihai;  Li, Xiaowei 收藏  |  浏览/下载：41/0  |  提交时间：2020/12/10 Convolutional neural networks  accelerator architecture  hardware acceleration
	Promoting the Harmony between Sparsity and Regularity: A Relaxed Synchronous Architecture for Convolutional Neural Networks 期刊论文 IEEE TRANSACTIONS ON COMPUTERS, 2019, 卷号: 68, 期号: 6, 页码: 867-881 作者:  Lu, Wenyan;  Yan, Guihai;  Li, Jiajun;  Gong, Shijun;  Jiang, Shuhao;  Wu, Jingya;  Li, Xiaowei 收藏  |  浏览/下载：249/0  |  提交时间：2019/08/16 Convolutional neural networks  accelerator  architecture  parallelism  sparsity
	SynergyFlow: An Elastic Accelerator Architecture Supporting Batch Processing of Large-Scale Deep Neural Networks 期刊论文 ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS, 2019, 卷号: 24, 期号: 1, 页码: 27 作者:  Li, Jiajun;  Yan, Guihai;  Lu, Wenyan;  Gong, Shijun;  Jiang, Shuhao;  Wu, Jingya;  Li, Xiaowei 收藏  |  浏览/下载：70/0  |  提交时间：2019/04/03 Deep neural networks  convolutional neural networks  accelerator  architecture  resource utilization  complementary effect