Madsen, Jan5; Stidsen, Thomas K.6; Kjærulff, Peter7; Mahadevan, Shankar2
1 Computer Science and Engineering, Department of Informatics and Mathematical Modeling, Technical University of Denmark2 Department of Informatics and Mathematical Modeling, Technical University of Denmark3 Operations Research, Department of Informatics and Mathematical Modeling, Technical University of Denmark4 Arcanic A/S, Technical University of Denmark5 Copenhagen Center for Health Technology, Center, Technical University of Denmark6 Department of Management Engineering, Technical University of Denmark7 Office for Study Programmes and Student Affairs, Administration, Technical University of Denmark
In this paper we present a multi-objective genetic algorithm to solve the problem of mapping a set of task graphs onto a heterogeneous multiprocessor platform. The objective is to meet all real-time deadlines subject to minimizing system cost and power consumption, while staying within bounds on local memory sizes and interface buffer sizes. Our approach allows for mapping onto a fixed platform or onto a flexible platform where architectural changes are explored during the mapping. We demonstrate our approach through an exploration of a smart phone, where five task graphs with a total of 530 tasks after hyper period extension are mapped onto a multiprocessor platform. The results show four non-inferior solutions which tradeoffs the various objectives.
Main Research Area:
Informatics and Mathematical Modelling, Technical University of Denmark, DTU, 2006