Early performance estimation of image compression methods on soft processors

Adam Powell, Christos-Savvas Bouganis, Peter Y. K. Cheung

Abstract: This paper presents a power and execution time estimation framework for an FPGA-based soft processor when considering the implementation of image compression techniques. Using the proposed framework, a quick power consumption and execution time estimate can be obtained early in the design phase allowing system designers to estimate these performance metrics without the need of implementing the algorithm or generating all possible soft processor architectures. This estimate is performed using both high-level algorithm parameters and soft processor architecture parameters. For system designers this can result in fast design space exploration. The model can predict the execution time of an algorithm with an average of 139% less relative error than predictions using only architecture parameters with the same framework.