This paper explores the role of data analysis methods to support system-level designers in characterising the performance of embedded applications. In particular, we address the performance modelling of software applications running on an embedded microprocessor. We propose a data analysis method, which, on the basis of a parameterisation of the software functionality and the hardware architecture, is able to predict the number of execution cycles on an embedded processor. Experiments with standard computational code (sorting, mathematical computation) and with MPEG variable length decoding are presented to support this claim.
['Gianluca Bontempi', 'Wido Kruijtzer']
A Data Analysis Method for Software Performance Prediction