Future Generation Computer Systems
Leakage power modeling and optimization in interconnection networks
Proceedings of the 2003 international symposium on Low power electronics and design
A Two-step Genetic Algorithm for Mapping Task Graphs to a Network on Chip Architecture
DSD '03 Proceedings of the Euromicro Symposium on Digital Systems Design
SUNMAP: a tool for automatic topology selection and generation for NoCs
Proceedings of the 41st annual Design Automation Conference
Exploiting the Routing Flexibility for Energy/Performance Aware Mapping of Regular NoC Architectures
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Energy-aware mapping for tile-based NoC architectures under performance constraints
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Artificial Bee Colony Programming Made Faster
ICNC '09 Proceedings of the 2009 Fifth International Conference on Natural Computation - Volume 04
Throughput-oriented NoC topology generation and analysis for high performance SoCs
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Energy- and Latency-Aware NoC Mapping Based on Chaos Discrete Particle Swarm Optimization
CMC '10 Proceedings of the 2010 International Conference on Communications and Mobile Computing - Volume 01
Energy- and performance-aware mapping for regular NoC architectures
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A multi-objective mapping strategy for application specific emesh network-on-chip (noc)
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Artificial bee colony algorithm: a survey
International Journal of Advanced Intelligence Paradigms
| Hi-index | 0.00 |
A new mapping algorithm is proposed based on Artificial Bee Colony (ABC) model to solve the problem of energy aware mapping optimization in Network-on-Chip (NoC) design. The optimal mapping result can be achieved by transmission of the information among various individuals. The comparison of the proposed algorithm with Genetic Algorithm (GA) and Max-Min Ant System (MMAS) based mapping algorithm shows that the new algorithm has lower energy consumption and faster convergence rate. Simulations are carried out and the results show the ABC based method could save energy by 15.5% in MMS, 5.1% in MPEG-4 decoder and 12.9% in VOPD compared to MMAS, respectively.