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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 6
1801-1806

CNN multidimensional fusion data reuse method for reconfigurable arrays

Zhang Xiaofana
Jiang Linb
Li Yuanchengb
Sheng Mingweib
a. College of Communication & Information Technology, b. College of Computer Science & Technology, Xi'an University of Science & Techno-logy, Xi'an 710600, China
DOI: 10.19734/j.issn.1001-3695.2024.10.0418

Abstract

Reconfigurable array architectures combine the flexibility of general-purpose processors with the high energy efficiency of dedicated hardware, making them an ideal solution for computation- and memory-intensive applications such as con-volutional neural network(CNN). However, increasing computational demands raise memory access overhead, limiting efficiency gains. To address this, this paper proposed a CNN-oriented multidimensional data reuse method for reconfigurable arrays. By utilizing intra-computing-unit data cyclic reuse and inter-unit data pulsation transfer, it achieved data reuse across both computing units and array dimensions. Task switching was enabled through array reconfiguration to facilitate multidimensional data reuse. Experimental results on the Virtex UltraScale 440 board show that this method reduces memory access by up to 69.4%, improves computational speed by over 16.2%, and achieves a computing unit utilization rate of 94.1%. These results demonstrate that this method enhances data reuse for CNN on reconfigurable arrays, enabling efficient hardware accele-ration.

Foundation Support

新一代人工智能国家科技重大专项资助项目(2022ZD0119005)
国家自然科学基金重点资助项目(61834005)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.10.0418
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 6
Section: System Development & Application
Pages: 1801-1806
Serial Number: 1001-3695(2025)06-027-1801-06

Publish History

[2025-03-06] Accepted Paper
[2025-06-05] Printed Article

Cite This Article

张骁帆, 蒋林, 李远成, 等. 面向可重构阵列的CNN多维融合数据复用方法 [J]. 计算机应用研究, 2025, 42 (6): 1801-1806. (Zhang Xiaofan, Jiang Lin, Li Yuancheng, et al. CNN multidimensional fusion data reuse method for reconfigurable arrays [J]. Application Research of Computers, 2025, 42 (6): 1801-1806. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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