Framework for rapid performance estimation of embedded soft core processors

Abstract

The large number of embedded soft core processors available today make it tedious and time consuming to select the best processor for a given application. This task is even more challenging due to the numerous configuration options available for a single soft core processor while optimizing for contradicting design requirements such as performance and area. In this article, we propose a generic framework for rapid performance estimation of applications on soft core processors. The proposed technique is scalable to the large number of configuration options available in modern soft core processors by relying on rapid and accurate estimation models instead of time-consuming FPGA synthesis and execution-based techniques. Experimental results on two leading commercial soft core processors executing applications from the widely used CHStone benchmark suite show an average error of less than 6% while running in the order of minutes when compared to hours taken by synthesis-based techniques.