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The AMPERE Project: A Model-driven development framework for highly Parallel and EneRgy-Efficient computation supporting multi-criteria optimization
Ref: CISTER-TR-200712       Publication Date: 19, May, 2020

The AMPERE Project: A Model-driven development framework for highly Parallel and EneRgy-Efficient computation supporting multi-criteria optimization

Ref: CISTER-TR-200712       Publication Date: 19, May, 2020

Abstract:
The high-performance requirements needed to implement the most advanced functionalities of current and future Cyber-Physical Systems (CPSs) are challenging the development processes of CPSs. On one side, CPSs rely on model-driven engineering (MDE) to satisfy the non-functional constraints and to ensure a smooth and safe integration of new features. On the other side, the use of complex parallel and heterogeneous embedded processor architectures becomes mandatory to cope with the performance requirements. In this regard, parallel programming models, such as OpenMP or CUDA, are a fundamental brick to fully exploit the performance capabilities of these architectures. However, parallel programming models are not compatible with current MDE approaches, creating a gap between the MDE used to develop CPSs and the parallel programming models supported by novel and future embedded platforms. The AMPERE project will bridge this gap by implementing a novel software architecture for the development of advanced CPSs. To do so, the proposed software architecture will be capable of capturing the definition of the components and communications described in the MDE framework, together with the non-functional properties, and transform it into key parallel constructs present in current parallel models, which may require extensions. These features will allow for making an efficient use of underlying parallel and heterogeneous architectures, while ensuring compliance with non-functional requirements, including those on real-time performance of the system.

Authors:
Eduardo Quiñones
,
Sara Royuela
,
Claudio Scordino
,
Paolo Gai
,
Luis Miguel Pinho
,
Luis Miguel Nogueira
,
Jan Rollo
,
Tommaso Cucinotta
,
Alessandro Biondi
,
Arne Hamann
,
Dirk Ziegenbein
,
Hadi Saoud
,
Romain Soulat
,
Björn Forsberg
,
Luca Benini
,
Gianluca Mandò
,
Luigi Rucher


Events:

ISORC 2020
19, May, 2020 >> 21, May, 2020
23rd IEEE International Symposium on Real-Time Distributing Computing
Online


23rd IEEE International Symposium on Real-Time Distributed Computing (ISORC 2020), pp 201-206.
Online.

DOI:10.1109/ISORC49007.2020.00042.
ISBN: 978-1-7281-6958-3.
ISSN: 2375-5261.



Record Date: 28, Jul, 2020