Improving system level design space exploration by incorporating SAT-solvers into multi-objective evolutionary algorithms

Schlichter T, Lukasiewycz M, Haubelt C, Teich J (2006)


Publication Status: Published

Publication Type: Conference contribution, Conference Contribution

Publication year: 2006

Book Volume: 2006

Pages Range: 309-314

Article Number: 1602457

Conference Proceedings Title: Proceedings of IEEE Computer Society Annual Symposium on VLSI. Karlsruhe

Event location: Klarlsruhe DE

ISBN: 9780769525334

DOI: 10.1109/ISVLSI.2006.57

Abstract

Automatic design space exploration at the system level is the task of finding optimal or close to optimal mappings for a set of applications onto an optimized architecture. Especially, finding a feasible binding of processes onto resources that permit the communications imposed by data dependencies is known to be a NP-complete task which demands the use of heuristic optimization approaches. Nearly all optimization approaches known from literature will fail in design spaces containing only a few feasible solutions. In this paper, we propose a novel approach based on the combination of Multi-Objective Evolutionary Algorithms and SAT-solvers to overcome these drawbacks. We will provide experimental results showing the efficiency of our novel methodology for synthetic and real life test cases. © 2006 IEEE.

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APA:

Schlichter, T., Lukasiewycz, M., Haubelt, C., & Teich, J. (2006). Improving system level design space exploration by incorporating SAT-solvers into multi-objective evolutionary algorithms. In Proceedings of IEEE Computer Society Annual Symposium on VLSI. Karlsruhe (pp. 309-314). Klarlsruhe, DE.

MLA:

Schlichter, Thomas, et al. "Improving system level design space exploration by incorporating SAT-solvers into multi-objective evolutionary algorithms." Proceedings of the IEEE Computer Society Annual Symposium on Emerging VLSI Technologies and Architectures 2006, Klarlsruhe 2006. 309-314.

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