The paper presents an object detection accelerator featuring a processing-in-memory (PIM) architecture on FPGAs. PIM architectures are well known for their energy efficiency and avoidance of the memory wall. In the accelerator, a PIM unit is developed using BRAM and LUT based counters, which also helps to improve the DSP performance density. The overall architecture consists of 64 PIM units and three memory buffers to store inter-layer results. A shrunk and quantized Tiny-YOLO network is mapped to the PIM accelerator, where DRAM access is fully eliminated during inference. The design achieves a throughput of 201.6 GOPs at 100MHz clock rate and correspondingly, a performance density of 0.57 GOPS/DSP.

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Wang HWang JHu HLi GHu SYu QLiu ZChen TZhou SLiu Y(2023)Ultra-High-Speed Accelerator Architecture for Convolutional Neural Network Based on Processing-in-Memory Using Resistive Random Access MemorySensors10.3390/s2305240123:5(2401)Online publication date: 21-Feb-2023
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Schizas NKarras AKarras CSioutas S(2022)TinyML for Ultra-Low Power AI and Large Scale IoT Deployments: A Systematic ReviewFuture Internet10.3390/fi1412036314:12(363)Online publication date: 6-Dec-2022
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ASPDAC '21: Proceedings of the 26th Asia and South Pacific Design Automation Conference

January 2021

930 pages

ISBN:9781450379991

DOI:10.1145/3394885

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Published: 29 January 2021

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Wang HWang JHu HLi GHu SYu QLiu ZChen TZhou SLiu Y(2023)Ultra-High-Speed Accelerator Architecture for Convolutional Neural Network Based on Processing-in-Memory Using Resistive Random Access MemorySensors10.3390/s2305240123:5(2401)Online publication date: 21-Feb-2023
https://doi.org/10.3390/s23052401
Schizas NKarras AKarras CSioutas S(2022)TinyML for Ultra-Low Power AI and Large Scale IoT Deployments: A Systematic ReviewFuture Internet10.3390/fi1412036314:12(363)Online publication date: 6-Dec-2022
https://doi.org/10.3390/fi14120363
Yang TJia QTao XHuang H(2022)Implementation and Optimization of Target Detection based on Multi-core DSP2022 IEEE 10th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)10.1109/ITAIC54216.2022.9836526(1587-1592)Online publication date: 17-Jun-2022
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Wang SWang SJiao BYang DSu LZhai PChen CZhang L(2022)CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in Space2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS47612.2022.9981172(10627-10634)Online publication date: 23-Oct-2022
https://doi.org/10.1109/IROS47612.2022.9981172
Ray P(2022)A review on TinyML: State-of-the-art and prospectsJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2021.11.01934:4(1595-1623)Online publication date: Apr-2022
https://doi.org/10.1016/j.jksuci.2021.11.019
Ren HDorofeev KAnicic DHammad YEckl RRunkler T(2022)SeLoC-ML: Semantic Low-Code Engineering for Machine Learning Applications in Industrial IoTThe Semantic Web – ISWC 202210.1007/978-3-031-19433-7_48(845-862)Online publication date: 16-Oct-2022
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An FPGA-based RNN-T Inference Accelerator with PIM-HBM

FPGA-based accelerator for object detection: a comprehensive survey

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