Enabling Cloud-Based Computational Fluid Dynamics With a Platform-as-a-Service Solution
| Autor: | Tamas Kiss, Gabor Terstyanszky, Nicola Fantini, Anastasia Anagnostou, Péter Kacsuk, Joris Costes, Simon J. E. Taylor, Djamel Lakehal |
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| Jazyk: | angličtina |
| Předmět: |
Product design
Computer science business.industry Distributed computing Platform as a service fluid mechanics 020208 electrical & electronic engineering cloud computing Cloud computing 02 engineering and technology Computational fluid dynamics Supercomputer Electronic mail Computer Science Applications high performance computing Workflow modeling and simulation Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business Information Systems |
| Zdroj: | IEEE Transactions on Industrial Informatics |
| ISSN: | 1941-0050 1551-3203 |
| DOI: | 10.1109/tii.2018.2849558 |
| Popis: | Computational fluid dynamics (CFD) is widely used in manufacturing and engineering from product design to testing. CFD requires intensive computational power and typically needs high-performance computing to reduce potentially long experimentation times. Dedicated high-performance computing systems are often expensive for small-to-medium enterprises (SMEs). Cloud computing claims to enable low-cost access to high-performance computing without the need for capital investment. The cloud-based simulation platform for manufacturing and engineering simulation platform aims to provide a flexible and easy to use cloud-based platform-as-a-service (PaaS) technology that can enable SMEs to realize the benefits of high-performance computing. Our platform incorporates workflow management and multicloud implementation across various cloud resources. Here, we present the components of our technology and experiences in using it to create a cloud-based version of the Transport phenomena Analysis Tool CFD software. Three case studies favourably compare the performance of a local cluster and two different clouds and demonstrate the viability of our cloud-based approach. |
| Databáze: | OpenAIRE |
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