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.…
Author details: | Kai Neubauer, Philipp WankoORCiDGND, Torsten SchaubORCiDGND, Christian HaubeltORCiD |
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DOI: | https://doi.org/10.23919/DATE.2018.8342014 |
ISBN: | 978-3-9819-2630-9 |
ISSN: | 1530-1591 |
ISSN: | 1558-1101 |
Title of parent work (English): | Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE) |
Publisher: | IEEE |
Place of publishing: | New York |
Publication type: | Other |
Language: | English |
Date of first publication: | 2018/04/23 |
Publication year: | 2018 |
Release date: | 2022/03/28 |
Number of pages: | 4 |
First page: | 257 |
Last Page: | 260 |
Funding institution: | German Science Foundation (DFG)German Research Foundation (DFG) [HA 4463/4-1, SCHA 550/11-1] |
Organizational units: | Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH |
DDC classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke |