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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 11
3353-3357

Deep learning platform architecture and key technologies

Shu Jian1,2,3
Chen Jianbo1,2
1. FLYTEK Research, IFLYTEK Co. , Ltd. , Hefei 230088, China
2. State Key Laboratory of Cognitive Intelligence, Hefei 230088, China
3. School of Computer Science & Technology, University of Science & Technology of China, Hefei 230026, China
DOI: 10.19734/j.issn.1001-3695.2023.03.0111

Abstract

In view of AI model production and training, the traditional script based physical server or cluster mode has pro-blems such as training inference separated, insufficient resource utilization, difficult migration of computing environment, and lengthy training process. This paper proposed a platform architecture for deep learning model training, the architecture divided into four layers: data platform layer, computing platform layer, training suite layer, and management platform layer. Firstly, it proposed an integrated framework masks differences in network structures and optimized the graphs. Secondly, it researched an adaptive resource matching mechanism based on GPU state reduced communication costs. At the same time, it improved resource utilization by providing a heuristic algorithm based label matching scheduling algorithm. Moreover, the establishment of tenant management and disaster recovery mechanisms ensured the safety and reliability of the system platform. Finally, it established the va-lidation of the usability, safety, reliability, and scalability through the simulation platform. Through the construction of deep learning platform, it will accelerate the implementation of AI production and promote the prosperity and development of AI technology and ecology.

Foundation Support

国家自然科学基金重点项目(72131006)
合肥市博士后科研活动项目经费(20210901)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.03.0111
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 11
Section: System Development & Application
Pages: 3353-3357
Serial Number: 1001-3695(2023)11-023-3353-05

Publish History

[2023-05-31] Accepted Paper
[2023-11-05] Printed Article

Cite This Article

束柬, 陈剑波. 深度学习平台体系架构及其关键技术 [J]. 计算机应用研究, 2023, 40 (11): 3353-3357. (Shu Jian, Chen Jianbo. Deep learning platform architecture and key technologies [J]. Application Research of Computers, 2023, 40 (11): 3353-3357. )

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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