A framework for evaluating design tradeoffs in packet processing architectures
Proceedings of the 39th annual Design Automation Conference
Towards efficient design space exploration of heterogeneous embedded media systems
Embedded processor design challenges
Multi-objective design space exploration using genetic algorithms
Proceedings of the tenth international symposium on Hardware/software codesign
An evolutionary approach to system-level synthesis
CODES '97 Proceedings of the 5th International Workshop on Hardware/Software Co-Design
A software framework for efficient system-level performance evaluation of embedded systems
Proceedings of the 2003 ACM symposium on Applied computing
Multicriteria Optimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
TDMA Time Slot and Turn Optimization with Evolutionary Search Techniques
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Methods for evaluating and covering the design space during early design development
Integration, the VLSI Journal
A Systematic Approach to Exploring Embedded System Architectures at Multiple Abstraction Levels
IEEE Transactions on Computers
System-Level Design Methodology with Direct Execution For Multiprocessors on SoPC
ISQED '06 Proceedings of the 7th International Symposium on Quality Electronic Design
A framework for system-level modeling and simulation of embedded systems architectures
EURASIP Journal on Embedded Systems
Analyzing concurrency in streaming applications
Journal of Systems Architecture: the EUROMICRO Journal
A mapping framework for guided design space exploration of heterogeneous MP-SoCs
Proceedings of the conference on Design, automation and test in Europe
Signature-Based Calibration of Analytical System-Level Performance Models
SAMOS '08 Proceedings of the 8th international workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation
A Mapping Framework Based on Packing for Design Space Exploration of Heterogeneous MPSoCs
Journal of Signal Processing Systems
Mapping and performance evaluation for heterogeneous MP-SoCs via packing
SAMOS'07 Proceedings of the 7th international conference on Embedded computer systems: architectures, modeling, and simulation
Design space abstraction and metamodeling for embedded systems design space exploration
Proceedings of the 7th International Workshop on Model-Based Methodologies for Pervasive and Embedded Software
Dimensioning heterogeneous MPSoCs via parallelism analysis
Proceedings of the Conference on Design, Automation and Test in Europe
A case for visualization-integrated system-level design space exploration
SAMOS'05 Proceedings of the 5th international conference on Embedded Computer Systems: architectures, Modeling, and Simulation
Transactions on High-Performance Embedded Architectures and Compilers IV
Energy- and reliability-aware task scheduling onto heterogeneous MPSoC architectures
The Journal of Supercomputing
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In the Sesame framework, we develop a modeling and simulation environment for the efficient design space exploration of heterogeneous embedded systems. Since Sesame recognizes separate application and architecture models within a single system simulation, it needs an explicit mapping step to relate these models for co-simulation. So far in Sesame, the mapping decision has been assumed to be made by an experienced designer, intuitively. However, this assumption is increasingly becoming inappropriate for the following reasons: already the realistic systems are far too complex for making intuitive decisions at an early design stage where the design space is very large. Likely, these systems will even get more complex in the near future. Besides, there exist multiple criteria to consider, like processing times, power consumption and cost of the architecture, which make the decision problem even harder.In this paper, the mapping decision problem is formulated as a multiobjective combinatorial optimization problem. For a solution approach, an optimization software tool, implementing an evolutionary algorithm from the literature, has been developed to achieve a set of best alternative mapping decisions under multiple criteria. In a case study, we have used our optimization tool to obtain a set of mapping decisions, some of which were further evaluated by the Sesame simulation framework.