@inproceedings{b450cb84c5a14deb8db0251429337378,
title = "Code generation of graph-based vision processing for multiple CUDA Cores SoC Jetson TX",
abstract = "Embedded vision processing is currently ingrained into many aspects of modern life, from computer-aided surgeries to navigation of unmanned aerial vehicles. Vision processing can be described using coarse-grained data flow graphs, which were standardized by OpenVX to enable both system and kernel level optimization via separation of concerns. Notably, graph-based specification provides a gateway to a code generation engine, which can produce an optimized, hardware-specific code for deployment. Here we provide an algorithm and JAVA-MVC-based implementation of automated code generation engine for OpenVX-based vision applications, tailored to NVIDIA multiple CUDA Cores SoC Jetson TX. Our algorithm pre-processes the graph, translates it into an ordered layer-oriented data model, and produces C code, which is optimized for the Jetson TX1 and comprised of error checking and iterative execution for real time vision processing.",
keywords = "Embedded computer vision, OpenVX, Visual programming",
author = "Elyassaf Madar and Natan Danan and {Ezra Tsur}, Elishai",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 12th IEEE International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2018 ; Conference date: 12-09-2018 Through 14-09-2018",
year = "2018",
month = nov,
day = "16",
doi = "10.1109/MCSoC2018.2018.00013",
language = "الإنجليزيّة",
series = "Proceedings - 2018 IEEE 12th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--7",
booktitle = "Proceedings - 2018 IEEE 12th International Symposium on Embedded Multicore/Many-Core Systems-on-Chip, MCSoC 2018",
address = "الولايات المتّحدة",
}