A new genetic simulated annealing algorithm for hardware-software partitioning
ABSTRACT To solve the hardware/software partitioning problem in embedded system, this paper proposed a new genetic simulated annealing algorithm (NGSA) which based on analysis of genetic algorithms and simulated annealing algorithm the main advantages and disadvantages. The genetic algorithm integrates the simulated annealing idea; niche technology is introduced to maintain population diversity; and the Metropolis criterion with the formation of new groups to improve the quality of group. Experimental results show that the algorithm has strong climbing ability and global search capability, and the fitness value is significantly improved than genetic algorithm and simulated annealing algorithm.
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ABSTRACT: A new niching genetic algorithm (NGA) called self-adaptive NGA (SANGA) is proposed. The main innovation is that the niche radius is estimated as an additional variable of the optimization problem and is not assigned a priori, as is usually done in other standard NGAs. SANGA, coupled with the deterministic pattern search method, forms a hybrid optimization method which works well in the optimization of multimodal functions and in the design of electromagnetic devicesIEEE Transactions on Magnetics 05/2006; · 1.42 Impact Factor
Conference Paper: TGFF: task graphs for free[Show abstract] [Hide abstract]
ABSTRACT: We present a user-controllable, general-purpose, pseudorandom task graph generator called Task Graphs For Free (TGFF). TGFF creates problem instances for use in allocation and scheduling research. It has the ability to generate independent tasks as well as task sets which are composed of partially ordered task graphs. A complete description of a scheduling problem instance is created, including attributes for processors, communication resources, tasks, and inter-task communication. The user may parametrically control the correlations between attributes. Sharing TGFF's parameter settings allows researchers to easily reproduce the examples used by others, regardless of the platform on which TGFF is runHardware/Software Codesign, 1998. (CODES/CASHE '98) Proceedings of the Sixth International Workshop on; 04/1998
Conference Paper: Hardware Software Partitioning Using Genetic Algorithm.[Show abstract] [Hide abstract]
ABSTRACT: Hardware software co-design is gaining importance with the advent of CAD for embedded systems. A key phase in such designs is partitioning the specification into hardware and software implementation sets. The problem being combinatorically explosive, several greedy search algorithms have been proposed for hardware software partitioning. In this paper, we model the hardware software partitioning problem as a Constraint Satisfaction Problem (CSP), and present a genetic algorithm based approach to solve the CSP in order to obtain the partitioning solution10th International Conference on VLSI Design (VLSI Design 1997), 4-7 January 1997, Hyderabad, India; 01/1997