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Boosting the Performance of Object Tracking with a Half-Precision Particle Filter on GPU
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0009-0003-6504-7109
Chulalongkorn University, Bangkok, Thailand.
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0002-1434-3042
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Computational Science and Technology (CST).ORCID iD: 0000-0003-0639-0639
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2024 (English)In: Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28 – September 1, 2023, Revised Selected Papers, Springer Nature , 2024, p. 294-305Conference paper, Published paper (Refereed)
Abstract [en]

High-performance GPU-accelerated particle filter methods are critical for object detection applications, ranging from autonomous driving, robot localization, to time-series prediction. In this work, we investigate the design, development and optimization of particle-filter using half-precision on CUDA cores and compare their performance and accuracy with single- and double-precision baselines on Nvidia V100, A100, A40 and T4 GPUs. To mitigate numerical instability and precision losses, we introduce algorithmic changes in the particle filters. Using half-precision leads to a performance improvement of 1.5–2 × and 2.5–4.6 × with respect to single- and double-precision baselines respectively, at the cost of a relatively small loss of accuracy.

Place, publisher, year, edition, pages
Springer Nature , 2024. p. 294-305
Keywords [en]
GPUs, Half-Precision, Particle Filter, Reduced Precision
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-346540DOI: 10.1007/978-3-031-50684-0_23Scopus ID: 2-s2.0-85192268315OAI: oai:DiVA.org:kth-346540DiVA, id: diva2:1858456
Conference
International workshops held at the 29th International Conference on Parallel and Distributed Computing, Euro-Par 2023, Aug 28 2023 - Sep 1 2023 Limassol, Cyprus
Note

Part of proceedings ISBN: 978-303150683-3

QC 20240520

Available from: 2024-05-16 Created: 2024-05-16 Last updated: 2024-05-20Bibliographically approved

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Schieffer, GabinAraújo De Medeiros, DanielMarkidis, StefanoWahlgren, JacobPeng, Ivy Bo

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