Automated Systolic Array Architecture Synthesis for High Throughput CNN Inference on FPGAs-Reference-Cited by-同舟云学术

Automated Systolic Array Architecture Synthesis for High Throughput CNN Inference on FPGAs

Published:2017-06-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 54th Annual Design Automation Conference 2017
language:
Short-container-title:

Author:

Wei Xuechao¹,Yu Cody Hao²,Zhang Peng³,Chen Youxiang³,Wang Yuxin³,Hu Han³,Liang Yun⁴,Cong Jason⁵

Affiliation:

1. Center for Energy-efficient Computing and Applications, School of EECS, Peking University, China and Falcon Computing Solutions, Inc, Los Angeles, CA, USA and Falcon Computing, Solutions Inc.

2. Computer Science Department, University of California, Los Angeles, CA, USA and Falcon Computing Solutions, Inc, Los Angeles, CA, USA and Falcon Computing, Solutions Inc.

3. Falcon Computing Solutions, Inc, Los Angeles, CA, USA

4. Center for Energy-efficient Computing and Applications, School of EECS, Peking University, China

5. Center for Energy-efficient Computing and Applications, School of EECS, Peking University, China and Computer Science Department, University of California, Los Angeles, CA, USA and Falcon Computing Solutions, Inc, Los Angeles, CA, USA and Falcon Computing Solutions Inc. and Peking University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3061639.3062207

Reference29 articles.

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3. S. Chakradhar et al. "A Dynamically Configurable Coprocessor for Convolutional Neural Networks " ISCA 2010. 10.1145/1815961.1815993 S. Chakradhar et al. "A Dynamically Configurable Coprocessor for Convolutional Neural Networks " ISCA 2010. 10.1145/1815961.1815993

4. C. Farabet et al. "CNP: An FPGA-based processor for Convolutional Networks " in FPL 2009. C. Farabet et al. "CNP: An FPGA-based processor for Convolutional Networks " in FPL 2009.

5. M. Peemen et al. "Memory-centric accelerator design for Convolutional Neural Networks " in ICCD 2013. M. Peemen et al. "Memory-centric accelerator design for Convolutional Neural Networks " in ICCD 2013.

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