Overcoming Data Transfer Bottlenecks in FPGA-based DNN Accelerators via Layer Conscious Memory Management-Reference-Cited by-同舟云学术

Overcoming Data Transfer Bottlenecks in FPGA-based DNN Accelerators via Layer Conscious Memory Management

Published:2019-06-02 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 56th Annual Design Automation Conference 2019
language:
Short-container-title:

Author:

Wei Xuechao¹,Liang Yun²,Cong Jason³

Affiliation:

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

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

3. 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

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3316781.3317875

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2. U. Aydonat S. O'Connell D. Capalija A. Ling and G. Chiu. 2017. An OpenCL Deep Learning Accelerator on Arria 10. In FPGA. 10.1145/3020078.3021738 U. Aydonat S. O'Connell D. Capalija A. Ling and G. Chiu. 2017. An OpenCL Deep Learning Accelerator on Arria 10. In FPGA. 10.1145/3020078.3021738

3. Y. Chen J. He X. Zhang C. Hao and D. Chen. 2019. Cloud-DNN: An Open Framework for Mapping DNN Models to Cloud FPGAs. In FPGA. 10.1145/3289602.3293915 Y. Chen J. He X. Zhang C. Hao and D. Chen. 2019. Cloud-DNN: An Open Framework for Mapping DNN Models to Cloud FPGAs. In FPGA. 10.1145/3289602.3293915

4. H. Gao Z. Liu K. Q. Weinberger and L. van der Maaten. 2017. Densely Connected Convolutional Networks. In CVPR. H. Gao Z. Liu K. Q. Weinberger and L. van der Maaten. 2017. Densely Connected Convolutional Networks. In CVPR.

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