Leakage aware dynamic voltage scaling for real-time embedded systems
Proceedings of the 41st annual Design Automation Conference
Multiprocessor Resource Allocation for Hard-Real-Time Streaming with a Dynamic Job-Mix
RTAS '05 Proceedings of the 11th IEEE Real Time on Embedded Technology and Applications Symposium
Energy-efficient policies for embedded clusters
LCTES '05 Proceedings of the 2005 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
Mapping and configuration methods for multi-use-case networks on chips
ASP-DAC '06 Proceedings of the 2006 Asia and South Pacific Design Automation Conference
Leakage-Aware Energy-Efficient Scheduling of Real-Time Tasks in Multiprocessor Systems
RTAS '06 Proceedings of the 12th IEEE Real-Time and Embedded Technology and Applications Symposium
Online resource management in a multiprocessor with a network-on-chip
Proceedings of the 2007 ACM symposium on Applied computing
ACM Transactions on Embedded Computing Systems (TECS)
RTSS '07 Proceedings of the 28th IEEE International Real-Time Systems Symposium
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Power-Aware Mapping of Probabilistic Applications onto Heterogeneous MPSoC Platforms
RTAS '09 Proceedings of the 2009 15th IEEE Symposium on Real-Time and Embedded Technology and Applications
Energy minimization for periodic real-time tasks on heterogeneous processing units
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Proceedings of the Conference on Design, Automation and Test in Europe
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Multi-task dynamic mapping onto NoC-based MPSoCs
Proceedings of the 24th symposium on Integrated circuits and systems design
On the design space exploration through the Hellfire Framework
Journal of Systems Architecture: the EUROMICRO Journal
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Multi-Processor Systems-on-Chip (MPSoC) are an increasingly important design paradigm not only for mobile embedded systems but also for industrial applications such as automotive and avionic systems. Such systems typically execute multiple concurrent applications, with different execution modes. Modes define differences in functionality and computational resource demands and are assigned with an execution probability. We propose a dynamic mapping approach to maintain low power consumption over the system lifetime. Mapping templates for different application modes and execution probabilities are computed offline and stored on the system. At runtime a manager monitors the system and chooses an appropriate pre-computed template. Experiments show that our approach outperforms global static mapping approaches up to 45%.