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Executable modelling for highly parallel accelerators
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-0401-1036
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-5297-6548
2019 (English)In: Proceedings - 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 318-321, article id 8904827Conference paper, Published paper (Refereed)
Abstract [en]

High-performance embedded computing is developing rapidly since applications in most domains require a large and increasing amount of computing power. On the hardware side, this requirement is met by the introduction of heterogeneous systems, with highly parallel accelerators that are designed to take care of the computation-heavy parts of an application. There is today a plethora of accelerator architectures, including GPUs, many-cores, FPGAs, and domain-specific architectures such as AI accelerators. They all have their own programming models, which are typically complex, low-level, and involve explicit parallelism. This yields error-prone software that puts the functional safety at risk, unacceptable for safety-critical embedded applications. In this position paper we argue that high-level executable modelling languages tailored for parallel computing can help in the software design for high performance embedded applications. In particular, we consider the data-parallel model to be a suitable candidate, since it allows very abstract parallel algorithm specifications free from race conditions. Moreover, we promote the Action Language for fUML (and thereby fUML) as suitable host language.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2019. p. 318-321, article id 8904827
Keywords [en]
Alf, Data-parallelism, Executable models, FUML, High-performance computing, Modelling languages, Parallel programming, UML, Application programs, Modeling languages, Program processors, Safety engineering, Software design, Accelerator architectures, Data parallelism, Domain specific architectures, Embedded application, Executable model, Heterogeneous systems, High performance computing, C (programming language)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-46529DOI: 10.1109/MODELS-C.2019.00049Scopus ID: 2-s2.0-85075931548ISBN: 9781728151250 (print)OAI: oai:DiVA.org:mdh-46529DiVA, id: diva2:1379610
Conference
22nd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2019, 15 September 2019 through 20 September 2019
Available from: 2019-12-17 Created: 2019-12-17 Last updated: 2019-12-19Bibliographically approved

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Addazi, LorenzoCiccozzi, FedericoLisper, Björn

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