GPU-Accelerated Discrete Event Simulations: Towards Industry 4.0 Manufacturing

Moustafa Faheem; Adrian Murphy; Carlos Reano

doi:10.1109/ISCC53001.2021.9631514

GPU-Accelerated Discrete Event Simulations: Towards Industry 4.0 Manufacturing

Moustafa Faheem, Adrian Murphy, Carlos Reano

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Discrete Event Simulations (DES) are the most commonplace tools for modelling today's manufacturing factories and their processes. DES are becoming steadfastly integrated into their corresponding physical counterparts to administer greater avenues for their analysis, control, forecasts and optimisations in real-time. However, this growth does not materialise without a penalty in the form of computational burden. The demand for flexible and alternate approaches to accelerate DES is made necessary. Hence, the utilisation of GPUs to comply with such acceleration presents a research topic of growing interest. This work investigates the use of the Machine Learning platform TensorFlow with GPUs to accelerate a variety of manufacturing-domain DES using the SimPy simulation framework. A range of results were gathered, of speed-ups spanning between x1.4 and x3.21, paving the way for further enhancements towards the vision of real-time communication between simulation and physical system in the form of a complete Digital Twin.

Original language	English
Title of host publication	26th IEEE Symposium on Computers and Communications (ISCC 2021): Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	7
ISBN (Electronic)	9781665427449
DOIs	https://doi.org/10.1109/ISCC53001.2021.9631514
Publication status	Published - 15 Dec 2021
Event	26th IEEE Symposium on Computers and Communications 2021 - Athens, Greece Duration: 05 Sept 2021 → 08 Sept 2021 https://doi.org/10.1109/ISCC53001.2021

Publication series

Name	Proceedings: IEEE Symposium on Computers and Communications
Volume	2021-September
ISSN (Print)	1530-1346

Conference

Conference	26th IEEE Symposium on Computers and Communications 2021
Abbreviated title	ISCC
Country/Territory	Greece
City	Athens
Period	05/09/2021 → 08/09/2021
Internet address	https://doi.org/10.1109/ISCC53001.2021

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

ASJC Scopus subject areas

Software
Signal Processing
General Mathematics
Computer Science Applications
Computer Networks and Communications

Access to Document

10.1109/ISCC53001.2021.9631514Licence: Unspecified

Cite this

Faheem, M., Murphy, A., & Reano, C. (2021). GPU-Accelerated Discrete Event Simulations: Towards Industry 4.0 Manufacturing. In 26th IEEE Symposium on Computers and Communications (ISCC 2021): Proceedings (Proceedings: IEEE Symposium on Computers and Communications; Vol. 2021-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCC53001.2021.9631514

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title = "GPU-Accelerated Discrete Event Simulations: Towards Industry 4.0 Manufacturing",

abstract = "Discrete Event Simulations (DES) are the most commonplace tools for modelling today's manufacturing factories and their processes. DES are becoming steadfastly integrated into their corresponding physical counterparts to administer greater avenues for their analysis, control, forecasts and optimisations in real-time. However, this growth does not materialise without a penalty in the form of computational burden. The demand for flexible and alternate approaches to accelerate DES is made necessary. Hence, the utilisation of GPUs to comply with such acceleration presents a research topic of growing interest. This work investigates the use of the Machine Learning platform TensorFlow with GPUs to accelerate a variety of manufacturing-domain DES using the SimPy simulation framework. A range of results were gathered, of speed-ups spanning between x1.4 and x3.21, paving the way for further enhancements towards the vision of real-time communication between simulation and physical system in the form of a complete Digital Twin. ",

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Faheem, M , Murphy, A & Reano, C 2021, GPU-Accelerated Discrete Event Simulations: Towards Industry 4.0 Manufacturing. in 26th IEEE Symposium on Computers and Communications (ISCC 2021): Proceedings. Proceedings: IEEE Symposium on Computers and Communications, vol. 2021-September, Institute of Electrical and Electronics Engineers Inc., 26th IEEE Symposium on Computers and Communications 2021, Athens, Greece, 05/09/2021. https://doi.org/10.1109/ISCC53001.2021.9631514

GPU-Accelerated Discrete Event Simulations: Towards Industry 4.0 Manufacturing. / Faheem, Moustafa ; Murphy, Adrian ; Reano, Carlos.
26th IEEE Symposium on Computers and Communications (ISCC 2021): Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. (Proceedings: IEEE Symposium on Computers and Communications; Vol. 2021-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - GPU-Accelerated Discrete Event Simulations: Towards Industry 4.0 Manufacturing

AU - Faheem, Moustafa

AU - Murphy, Adrian

AU - Reano, Carlos

PY - 2021/12/15

Y1 - 2021/12/15

N2 - Discrete Event Simulations (DES) are the most commonplace tools for modelling today's manufacturing factories and their processes. DES are becoming steadfastly integrated into their corresponding physical counterparts to administer greater avenues for their analysis, control, forecasts and optimisations in real-time. However, this growth does not materialise without a penalty in the form of computational burden. The demand for flexible and alternate approaches to accelerate DES is made necessary. Hence, the utilisation of GPUs to comply with such acceleration presents a research topic of growing interest. This work investigates the use of the Machine Learning platform TensorFlow with GPUs to accelerate a variety of manufacturing-domain DES using the SimPy simulation framework. A range of results were gathered, of speed-ups spanning between x1.4 and x3.21, paving the way for further enhancements towards the vision of real-time communication between simulation and physical system in the form of a complete Digital Twin.

AB - Discrete Event Simulations (DES) are the most commonplace tools for modelling today's manufacturing factories and their processes. DES are becoming steadfastly integrated into their corresponding physical counterparts to administer greater avenues for their analysis, control, forecasts and optimisations in real-time. However, this growth does not materialise without a penalty in the form of computational burden. The demand for flexible and alternate approaches to accelerate DES is made necessary. Hence, the utilisation of GPUs to comply with such acceleration presents a research topic of growing interest. This work investigates the use of the Machine Learning platform TensorFlow with GPUs to accelerate a variety of manufacturing-domain DES using the SimPy simulation framework. A range of results were gathered, of speed-ups spanning between x1.4 and x3.21, paving the way for further enhancements towards the vision of real-time communication between simulation and physical system in the form of a complete Digital Twin.

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M3 - Conference contribution

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T3 - Proceedings: IEEE Symposium on Computers and Communications

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GPU-Accelerated Discrete Event Simulations: Towards Industry 4.0 Manufacturing

Abstract

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