CNN-MERP: An FPGA-based memory-efficient reconfigurable processor for forward and backward propagation of convolutional neural networks

Xushen Han, Dajiang Zhou, Shihao Wang, Shinji Kimura

研究成果: Conference contribution

26 被引用数 (Scopus)

抄録

Large-scale deep convolutional neural networks (CNNs) are widely used in machine learning applications. While CNNs involve huge complexity, VLSI (ASIC and FPGA) chips that deliver high-density integration of computational resources are regarded as a promising platform for CNN's implementation. At massive parallelism of computational units, however, the external memory bandwidth, which is constrained by the pin count of the VLSI chip, becomes the system bottleneck. Moreover, VLSI solutions are usually regarded as a lack of the flexibility to be reconfigured for the various parameters of CNNs. This paper presents CNN-MERP to address these issues. CNN-MERP incorporates an efficient memory hierarchy that significantly reduces the bandwidth requirements from multiple optimizations including on/off-chip data allocation, data flow optimization and data reuse. The proposed 2-level reconfigurability is utilized to enable fast and efficient reconfiguration, which is based on the control logic and the multiboot feature of FPGA. As a result, an external memory bandwidth requirement of 1.94MB/GFlop is achieved, which is 55% lower than prior arts. Under limited DRAM bandwidth, a system throughput of 1244GFlop/s is achieved at the Vertex UltraScale platform, which is 5.48 times higher than the state-of-the-art FPGA implementations.

本文言語English
ホスト出版物のタイトルProceedings of the 34th IEEE International Conference on Computer Design, ICCD 2016
出版社Institute of Electrical and Electronics Engineers Inc.
ページ320-327
ページ数8
ISBN(電子版)9781509051427
DOI
出版ステータスPublished - 2016 11 22
イベント34th IEEE International Conference on Computer Design, ICCD 2016 - Scottsdale, United States
継続期間: 2016 10 22016 10 5

出版物シリーズ

名前Proceedings of the 34th IEEE International Conference on Computer Design, ICCD 2016

Other

Other34th IEEE International Conference on Computer Design, ICCD 2016
国/地域United States
CityScottsdale
Period16/10/216/10/5

ASJC Scopus subject areas

  • ハードウェアとアーキテクチャ

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