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Exact multi-objective design space exploration using ASPmT

  • An efficient Design Space Exploration (DSE) is imperative for the design of modern, highly complex embedded systems in order to steer the development towards optimal design points. The early evaluation of design decisions at system-level abstraction layer helps to find promising regions for subsequent development steps in lower abstraction levels by diminishing the complexity of the search problem. In recent works, symbolic techniques, especially Answer Set Programming (ASP) modulo Theories (ASPmT), have been shown to find feasible solutions of highly complex system-level synthesis problems with non-linear constraints very efficiently. In this paper, we present a novel approach to a holistic system-level DSE based on ASPmT. To this end, we include additional background theories that concurrently guarantee compliance with hard constraints and perform the simultaneous optimization of several design objectives. We implement and compare our approach with a state-of-the-art preference handling framework for ASP. Experimental resultsAn efficient Design Space Exploration (DSE) is imperative for the design of modern, highly complex embedded systems in order to steer the development towards optimal design points. The early evaluation of design decisions at system-level abstraction layer helps to find promising regions for subsequent development steps in lower abstraction levels by diminishing the complexity of the search problem. In recent works, symbolic techniques, especially Answer Set Programming (ASP) modulo Theories (ASPmT), have been shown to find feasible solutions of highly complex system-level synthesis problems with non-linear constraints very efficiently. In this paper, we present a novel approach to a holistic system-level DSE based on ASPmT. To this end, we include additional background theories that concurrently guarantee compliance with hard constraints and perform the simultaneous optimization of several design objectives. We implement and compare our approach with a state-of-the-art preference handling framework for ASP. Experimental results indicate that our proposed method produces better solutions with respect to both diversity and convergence to the true Pareto front.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Kai Neubauer, Philipp WankoORCiD, Torsten H. SchaubORCiDGND, Christian HaubeltORCiD
DOI:https://doi.org/10.23919/DATE.2018.8342014
ISBN:978-3-9819-2630-9
ISSN:1530-1591
ISSN:1558-1101
Titel des übergeordneten Werks (Englisch):Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE)
Verlag:IEEE
Verlagsort:New York
Publikationstyp:Sonstiges
Sprache:Englisch
Datum der Erstveröffentlichung:23.04.2018
Erscheinungsjahr:2018
Datum der Freischaltung:28.03.2022
Seitenanzahl:4
Erste Seite:257
Letzte Seite:260
Fördernde Institution:German Science Foundation (DFG)German Research Foundation (DFG) [HA 4463/4-1, SCHA 550/11-1]
Organisationseinheiten:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC-Klassifikation:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
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