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Hybrid CPU-GPU acceleration of a multithreaded image stitching algorithm

Title	Hybrid CPU-GPU acceleration of a multithreaded image stitching algorithm
Author	Tesfay, Shewıt Weldu, Demirdağ, Zeynep Gülbeyaz, Uğurdağ, Hasan Fatih, Ates, H. F.
Publication Date:	2022
Publication Place	- IEEE
Subject	CPU-GPU, Image stitching, Multithreading, Real-time image processing
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-166547010-0
Record ID	a7576f77-d8c5-46b7-af3c-b5cb751deba2
Library Location	Electrical & Electronics Engineering
Date	2022
Notes	TÜBİTAK
Sample Text	Real-time image stitching is critical, especially in un-manned aerial vehicles, and its acceleration has received attention in recent years. This paper describes an image stitching acceleration scheme for heterogeneous (CPU+GPU) devices. Acceleration is attempted with both multithreading and multiprocessing. Most time-critical functions in the algorithm are offloaded on to the GPU. We crafted a 3-buffer ping-pong mechanism for synchro-nization and data transfer among threads/processes in order to maximize CPU utilization. We carried out our experiments on Nvidia Jetson AGX Xavier. Results show that more than 3x acceleration is achieved.
DOI	10.1109/UBMK55850.2022.9919473

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Özyeğin University

Hybrid CPU-GPU acceleration of a multithreaded image stitching algorithm

Author Tesfay, Shewıt Weldu, Demirdağ, Zeynep Gülbeyaz, Uğurdağ, Hasan Fatih, Ates, H. F.

Publication Date 2022

Publication Place - IEEE

Subject CPU-GPU, Image stitching, Multithreading, Real-time image processing

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-166547010-0

Record ID a7576f77-d8c5-46b7-af3c-b5cb751deba2

Library Location Electrical & Electronics Engineering

Date 2022

Notes TÜBİTAK

Sample Text Real-time image stitching is critical, especially in un-manned aerial vehicles, and its acceleration has received attention in recent years. This paper describes an image stitching acceleration scheme for heterogeneous (CPU+GPU) devices. Acceleration is attempted with both multithreading and multiprocessing. Most time-critical functions in the algorithm are offloaded on to the GPU. We crafted a 3-buffer ping-pong mechanism for synchro-nization and data transfer among threads/processes in order to maximize CPU utilization. We carried out our experiments on Nvidia Jetson AGX Xavier. Results show that more than 3x acceleration is achieved.

DOI 10.1109/UBMK55850.2022.9919473