@inproceedings{b016022757d8445893979ca0557c5910,
title = "An FPGA-GPU Heterogeneous System and Implementation for On-Board Remote Sensing Data Processing",
abstract = "In resource-constrained space environments, energy-efficient and high-performance processors like Field- Programmable Gate Arrays (FPGAs) and Digital Signal Processors (DSPs) are widely utilized for on-board data processing. However, the variety of tasks in space missions, including remote sensing data pre-processing and processing, reveals the limitations of single processors. To address this, we suggest a heterogeneous system that combines FPGAs with embedded Graphics Processing Unit (GPU) TX2 for efficient remote sensing data pre-processing and processing. Additionally, to overcome the challenges in data transfer between the FPGA and TX2, we utilized High-Level Synthesis (HLS) to design a dedicated IP for efficient data transfer between the FPGA and TX2 using PCIe protocol. This method enhances data transfer speeds and enables TX2 to manage address mapping in the Double Data Rate (DDR) memory. Our system successfully completes remote sensing data processing by integrating these elements.",
keywords = "FPGA, HLS, embedded GPU, heterogeneous system, remote sensing",
author = "Tingting Qiao and Yu Xie and He Chen and Yizhuang Xie",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 22nd International Conference on Field-Programmable Technology, ICFPT 2023 ; Conference date: 12-12-2023 Through 14-12-2023",
year = "2023",
doi = "10.1109/ICFPT59805.2023.00035",
language = "English",
series = "Proceedings - International Conference on Field-Programmable Technology, ICFPT",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "254--257",
booktitle = "Proceedings - 2023 International Conference on Field-Programmable Technology, ICFPT 2023",
address = "United States",
}