Efficient Implementation of DVI Protocol on FPGA

This paper presents a general-purpose hardware implementation of the digital visual interface (DVI) protocol on the Xilinx Virtex-6 ML605 FPGA platform for real-time display of digital processing results. The design enables direct output of processed data from the FPGA to an external monitor without relying on external processors or software-based rendering tools. It addresses key challenges in timing synchronization, pixel formatting, and interfacing with the onboard Chrontel CH7301C encoder to support resolutions up to 1920×1080 at 60 Hz. A lightweight processing pipeline is developed in Verilog to convert multidimensional outputs into a sequential stream of pixel data conforming to the DVI protocol. As a case study, a lightweight convolutional neural network trained on the CIFAR-10 dataset is implemented on the FPGA, and its classification probabilities are displayed as a probability map on an LCD. Experimental results confirm low resource utilization and real-time performance, validating the system’s applicability in embedded applications such as machine learning inference, image processing, and real- time monitoring. This work demonstrates the feasibility of FPGA- based platforms for efficiently displaying digital video output in intelligent edge systems.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-05-01
DOI
https://doi.org/10.22067/cke.2025.91345.1142
Primary Topic
Protein Tyrosine Phosphatases
Type
article
Field-Weighted Citation Impact
0.00
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article

Efficient Implementation of DVI Protocol on FPGA

SHILAP Revista de lepidopterología
Protein Tyrosine Phosphatases
article

Efficient Implementation of DVI Protocol on FPGA

article en

Abstract

This paper presents a general-purpose hardware implementation of the digital visual interface (DVI) protocol on the Xilinx Virtex-6 ML605 FPGA platform for real-time display of digital processing results. The design enables direct output of processed data from the FPGA to an external monitor without relying on external processors or software-based rendering tools. It addresses key challenges in timing synchronization, pixel formatting, and interfacing with the onboard Chrontel CH7301C encoder to support resolutions up to 1920×1080 at 60 Hz. A lightweight processing pipeline is developed in Verilog to convert multidimensional outputs into a sequential stream of pixel data conforming to the DVI protocol. As a case study, a lightweight convolutional neural network trained on the CIFAR-10 dataset is implemented on the FPGA, and its classification probabilities are displayed as a probability map on an LCD. Experimental results confirm low resource utilization and real-time performance, validating the system’s applicability in embedded applications such as machine learning inference, image processing, and real- time monitoring. This work demonstrates the feasibility of FPGA- based platforms for efficiently displaying digital video output in intelligent edge systems.

SHILAP Revista de lepidopterología
Ferdowsi University of Mashhad (IR)
Openalex Percentile: Top 49%
Protein Tyrosine Phosphatases
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