中文版 | English
Title

An Integer-Only and Group-Vector Systolic Accelerator for Efficiently Mapping Vision Transformer on Edge

Author
Corresponding AuthorYu, Hao
Publication Years
2023-10-01
DOI
Source Title
ISSN
1549-8328
EISSN
1558-0806
Abstract
Transformer-like network has shown remarkable high performance in both natural language processing and computer vision. However, the huge computational demands in non-linear floating-point arithmetic and the irregular memory access requirement in self-attention mechanism make it still a challenge to deploy Transformer on edge. To address the above issues, we propose integer-only quantization scheme for the simplification of non-linear operations (such as LayerNorm, Softmax and Gelu), meanwhile algorithm-hardware co-design strategy is applied to guarantee both the high accuracy and high efficiency. Besides, we construct general-purpose group vector systolic array to efficiently accelerate the matrix multiplication operations including both regular matrix-multiplication/convolution and the irregular multi-head self-attention mechanism. Unified data-package strategy and flexible on-/off-chip data storage management strategy are also proposed to further improve the performance. The design has been deployed on Xilinx ZCU102 FPGA platform, achieving an overall inference latency of 4.077ms and 11.15ms per image for ViT-tiny and ViT-s, respectively. The average throughput can reach as high as 762.7 GOPs, which shows significant improvement over the previous state-of-the-art FPGA Transformer accelerator.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Corresponding
Funding Project
STI 2030-Major Project[2022ZD0210600] ; National Natural Science Foundation of China (NSFC)[62034007] ; Shenzhen Science and Technology Program["KQTD20200820113051096","JCYJ20200109115210307"]
WOS Research Area
Engineering
WOS Subject
Engineering, Electrical & Electronic
WOS Accession No
WOS:001092405100001
Publisher
ESI Research Field
ENGINEERING
Data Source
Web of Science
Citation statistics
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/582737
DepartmentSUSTech Institute of Microelectronics
Affiliation
1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China
2.Southern Univ Sci & Technol, Sch Microelect, Shenzhen 518055, Peoples R China
Corresponding Author AffilicationSUSTech Institute of Microelectronics
Recommended Citation
GB/T 7714
Huang, Mingqiang,Luo, Junyi,Ding, Chenchen,et al. An Integer-Only and Group-Vector Systolic Accelerator for Efficiently Mapping Vision Transformer on Edge[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS,2023.
APA
Huang, Mingqiang,Luo, Junyi,Ding, Chenchen,Wei, Zikun,Huang, Sixiao,&Yu, Hao.(2023).An Integer-Only and Group-Vector Systolic Accelerator for Efficiently Mapping Vision Transformer on Edge.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS.
MLA
Huang, Mingqiang,et al."An Integer-Only and Group-Vector Systolic Accelerator for Efficiently Mapping Vision Transformer on Edge".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS (2023).
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