A framework for estimation and minimizing energy dissipation of embedded HW/SW systems
DAC '98 Proceedings of the 35th annual Design Automation Conference
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Wattch: a framework for architectural-level power analysis and optimizations
Proceedings of the 27th annual international symposium on Computer architecture
Energy-driven integrated hardware-software optimizations using SimplePower
Proceedings of the 27th annual international symposium on Computer architecture
Architectural and compiler techniques for energy reduction in high-performance microprocessors
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on low-power electronics and design
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Data Structures and Algorithms
Data Structures and Algorithms
Multi-objective design space exploration using genetic algorithms
Proceedings of the tenth international symposium on Hardware/software codesign
System-level design: orthogonalization of concerns and platform-based design
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Platune: a tuning framework for system-on-a-chip platforms
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Proceedings of the 2004 ACM symposium on Applied computing
Application-specific customization of parameterized FPGA soft-core processors
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Design space navigation for neighboring power-performance efficient microprocessor configurations
ARCS'05 Proceedings of the 18th international conference on Architecture of Computing Systems conference on Systems Aspects in Organic and Pervasive Computing
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In this paper, we address the problem of the efficient exploration of the architectural design space for parameterized systems. Since the design space is multi-objective, our aim is to find all the Pareto-optimal configurations that represent the best design trade-offs by varying the architectural parameters of the target system. In particular, the paper proposes a Design Space Exploration (DSE) framework based on a random search algorithm that has been tuned to efficiently derive Pareto-optimal curves. The reported design space exploration results have shown a reduction of the simulation time of up to two orders of magnitude with respect to full search strategy, while maintaining an average accuracy within 3%.