Accelerating applications with Vitis unified environment. Case study: Vitis Vision Library

Valido, Manuel J.; Castelló, Eduardo Magdaleno; Medina, Patricia Sanchez; González, Argelio Mauro

doi:10.1109/taee54169.2022.9840643

Cited by 1 publication

(1 citation statement)

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“…Xilinx offers a Vitis Accelerated Library that can be implemented in hardware and contains several computer vision functions for performing image processing [33]. The libraries use C/C++ for hardware description and can be synthesized in hardware with HLS into "Vitis Kernel" which can run in Xilinx FPGAs.…”

Section: Plmentioning

confidence: 99%

Memory-Tree Based Design of Optical Character Recognition in FPGA

Kim

Choi

2023

Electronics

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As one of the fields of Artificial Intelligence (AI), Optical Character Recognition (OCR) systems have wide application in both industrial production and daily life. Conventional OCR systems are commonly designed and implement data computation on the basis of microprocessors; the performance of the processor relates to the effect of the computation. However, due to the “Memory-wall” problem and Von Neumann bottlenecks, the drawbacks of traditional processor-based computing for OCR systems are gradually becoming apparent. In this paper, an approach based on the Memory-Centric Computing and “Memory-Tree” algorithm has been proposed to perform hardware optimization of traditional OCR systems. The proposed algorithm was first designed in software implementation using C/C++ and OpenCV to verify the feasibility of the idea and then the RTL conversion of the algorithm was done using the Xilinx Vitis High Level Synthesis (HLS) tool to implement the hardware. This work chose Xilinx Alveo U50 FPGA Accelerator to complete the hardware design, which can be connected to the x86 CPU in the PC by PCIe to form heterogeneous computing. The results of the hardware implementation show that the system this work designed can recognize characters of English capital letters and numbers within 34.24 us. The power of FPGA is 18.59 W, which saves 77.87% of energy consumption compared to the 84 W of the processor in PC.

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Section: Plmentioning

confidence: 99%