@inproceedings{f32348a66af14c769f9786b3937c92b8,
title = "VOTA: A 2.45TFLOPS/W Heterogeneous Multi-Core Visual Object Tracking Accelerator Based on Correlation Filters",
abstract = "VOTA is a domain-specific accelerator for correlation filter (CF)-based visual object tracking (VOT). It encompasses a Winograd convolution core, a FFT core and a vector core in a high-bandwidth starring topology. VOTA's frame-based instructions and execution enable a 537GFLOPS performance and reduce the code size. An instruction-chaining mechanism permits inter-core pipelining to improve the utilization to 84.2%. A 10.2mm2 28nm FP16 VOTA prototype incorporating a RISC-V host CPU is measured to achieve 2.45TFLOPS/W at 0.72V. Running OPCF, a CF-based VOT enhanced by adaptive boosting and particle filters, the chip achieves 1157FPS on 640×480 input frames at 0.9V and 175MHz, consuming 296mW.",
author = "Junkang Zhu and Wei Tang and Lee, {Ching En} and Haolei Ye and Eric McCreath and Zhengya Zhang",
note = "Publisher Copyright: {\textcopyright} 2021 JSAP.; 35th Symposium on VLSI Circuits, VLSI Circuits 2021 ; Conference date: 13-06-2021 Through 19-06-2021",
year = "2021",
month = jun,
day = "13",
doi = "10.23919/VLSICircuits52068.2021.9492379",
language = "English",
series = "IEEE Symposium on VLSI Circuits, Digest of Technical Papers",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 Symposium on VLSI Circuits, VLSI Circuits 2021",
address = "United States",
}