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 to 21, 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 to 21, May, 2020Abstract:
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.
Eduardo Quiñones
Luis Miguel Pinho
Luis Miguel NogueiraEvents:
Document:
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Download23rd 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