4922348
doi
10.5281/zenodo.4922348
oai:zenodo.org:4922348
user-up2date
user-eu
Leonidas Kosmidis
BSC
Carlos F. Nicolas
IKERLAN
Javier de Lasala
CAF
Ion LarraƱaga
CAF
Assessing and Improving the Suitability of Model-Based Design for GPU-Accelerated Railway Control Systems
Alejandro J. Calderon
IKERLAN
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Model-Based Design
GPU
Control Systems
<p>Model-Based Design (MBD) is widely used for the design and simulation of electric traction control systems in the railway industry.<br>
Moreover, similar to other transportation industries, railway is moving towards the consolidation of multiple computing systems on fewer and more powerful ones, aiming for the reduction of Size, Weight and Power (SWaP). In that regard, Graphics Processing Units (GPUs) are increasingly considered by critical systems engineers, seeking to satisfy their ever increasing performance requirements. Recently, MBD tools have been enhanced with GPU code generation capabilities for machine learning acceleration, however, there is no indication whether these tools are ready for the design of time-sensitive systems. In this paper we analyse<br>
the suitability of commercial MBD toolsets by designing and deploying a model-based parallel control case study on embedded GPU<br>
platforms. While our results show promising feasibility evidence, they also reveal shortcomings which should be addressed before these toolsets become fit for developing critical systems. We propose certain improvements that have to be incorporated in these tools to achieve this goal. By implementing our proposals in the generated code, we experimentally show their efectiveness on two NVIDIA-based embedded GPUs.</p>
This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ARCS 2021 (https://doi.org/10.1007/978-3-030-81682-7_5)
Zenodo
2021-06-07
info:eu-repo/semantics/conferencePaper
4922347
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user-eu
v1
award_title=Intelligent software-UPDATE technologies for safe and secure mixed-criticality and high performance cyber physical systems; award_number=871465; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/871465; funder_id=00k4n6c32; funder_name=European Commission;
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1107621
md5:80bc500646ba62c36ca160c0183e7102
https://zenodo.org/records/4922348/files/Assessing and Improving the Suitability of Model Based Design for GPU Accelerated Railway Control Systems.pdf
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10.5281/zenodo.4922347
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doi