Title

Uncertainty Model for Configurable Hardware/Software and Resource Partitioning

Published In

IEEE Transactions on Computers

Document Type

Citation

Publication Date

10-2016

Abstract

Automatic hardware/software partitioning relies on characterization, estimation and design space exploration of the system performance and cost metrics. In real world situations, such estimates are complicated and cannot be 100 percent accurate. Furthermore, hardware/software co-design is so complicated nowadays that simply considering the bipartitioning between hardware and software is not sufficient. It is important to consider some of the other key design parameters and resource sharing together with the hardware/software partitioning problem. Under variable requirements of smart systems, more flexibility on the resource usage should be incorporated in system modelling. This paper considers uncertainty modeling for system partitioning with an enhanced set of parameters for hardware/software resource sharing. We harness state-of-the-art uncertainty theory for linear uncertain distribution and normal uncertain distribution. Our derivations convert the uncertainty model back to a regular constraint optimization problem. Experimental results show the effectiveness of our approach.

Description

Paper originally appeared in IEEE Transactions on Computers (Volume: 65, Issue: 10 ).

© Copyright 2016 IEEE - All rights reserved.

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Unaffiliated researchers can access the work here: http://dx.doi.org/10.1109/TC.2016.2519895

DOI

10.1109/TC.2016.2519895

Persistent Identifier

http://archives.pdx.edu/ds/psu/18102

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