Evaluating the computational capabilities of embedded multicore and GPU platforms for on-board image processing

Cita com:
hdl:2117/405883
Document typeConference report
Defense date2023
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
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ProjectSuPerCom - Sustainable Performance for High-Performance Embedded Computing Systems (EC-H2020-772773)
METASAT - MODULAR MODEL-BASED DESIGN AND TESTING FOR APPLICATIONS IN SATELLITES (EC-HE-101082622)
BSC - COMPUTACION DE ALTAS PRESTACIONES VIII (AEI-PID2019-107255GB-C21)
METASAT - MODULAR MODEL-BASED DESIGN AND TESTING FOR APPLICATIONS IN SATELLITES (EC-HE-101082622)
BSC - COMPUTACION DE ALTAS PRESTACIONES VIII (AEI-PID2019-107255GB-C21)
Abstract
On-board Image Processing is one of the most computationally intensive tasks performed in space payload processing. With the constant increase in the resolution of optical sensors, new powerful architectures are needed for their processing. In this work, we evaluate the capabilities of several state-of-the-art embedded COTS and radiation tolerant multicore and GPU featuring platforms, with an open source on-board image processing application we have developed and parallelised. Our results show that both embedded multicores and especially GPUs are very effective for such tasks. In fact, GPUs become even more efficient when sensor sizes are increasing, making them ideal candidates for future space missions.
CitationRodriguez, I. [et al.]. Evaluating the computational capabilities of embedded multicore and GPU platforms for on-board image processing. A: European Data Handling & Data Processing Conference for Space. "Proceedings of the 2023 European Data Handling & Data Processing Conference for Space (EDHPC 2023)". Institute of Electrical and Electronics Engineers (IEEE), 2023. ISBN 978-9-09-037924-1. DOI 10.23919/EDHPC59100.2023.10395928.
ISBN978-9-09-037924-1
Publisher versionhttps://ieeexplore.ieee.org/document/10395928
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