Djemame, K orcid.org/0000-0001-5811-5263, Kavanagh, R orcid.org/0000-0002-9357-2459, Kelefouras, V et al. (9 more authors) (2018) Towards an Energy-Aware Framework for Application Development and Execution in Heterogeneous Parallel Architectures. In: Kachris, C, Falsafi, B and Soudris, D, (eds.) Hardware Accelerators in Data Centers. Springer , pp. 129-148. ISBN 9783319927916
Abstract
The Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation (TANGO) project’s goal is to characterise factors which affect power consumption in software development and operation for Heterogeneous Parallel Hardware (HPA) environments. Its main contribution is the combination of requirements engineering and design modelling for self-adaptive software systems, with power consumption awareness in relation to these environments. The energy efficiency and application quality factors are integrated into the application lifecycle (design, implementation and operation). To support this, the key novelty of the project is a reference architecture and its implementation. Moreover, a programming model with built-in support for various hardware architectures including heterogeneous clusters, heterogeneous chips and programmable logic devices is provided. This leads to a new cross-layer programming approach for heterogeneous parallel hardware architectures featuring software and hardware modelling. Application power consumption and performance, data location and time-criticality optimization, as well as security and dependability requirements on the target hardware architecture are supported by the architecture.
Metadata
Item Type: | Book Section |
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Copyright, Publisher and Additional Information: | © 2019 Springer International Publishing AG, part of Springer Nature. This is a post-peer-review, pre-copyedit version of a book chapter published in Hardware Accelerators in Data Centers. The final authenticated version is available online at https://doi.org/10.1007/978-3-319-92792-3_7 |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Jul 2019 13:59 |
Last Modified: | 22 Aug 2020 00:38 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-319-92792-3_7 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:149054 |