Retargetable profiling for rapid, early system-level design space exploration

Authors:
Lukai Cai;Andreas Gerstlauer;Daniel Gajski
Affiliations:
University of California, Irvine, CA;University of California, Irvine, CA;University of California, Irvine, CA
Venue:
Proceedings of the 41st annual Design Automation Conference
Year:
2004

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Abstract

Fast and accurate estimation is critical for exploration of any design space in general. As we move to higher levels of abstraction, estimation of complete system designs at each level of abstraction is needed. Estimation should provide a variety of useful metrics relevant to design tasks in different domains and at each stage in the design process.In this paper, we present such a system-level estimation approach based on a novel combination of dynamic profiling and static retargeting. Co-estimation of complete system implementations is fast while accurately reflecting even dynamic effects. Furthermore, retargetable profiling is supported at multiple levels of abstraction, providing multiple design quality metrics at each level. Experimental results show the applicability of the approach for efficient design space exploration.