A SW performance estimation framework for early system-level-design using fine-grained instrumentation

The increasing demands of high-performance in embedded applications under shortening time-to-market has prompted system architects in recent time to opt for multi-processor systems-on-chip (MP-SoCs) employing several programmable devices. The programmable cores provide a high amount of flexibility and reusability, and can be optimized to the requirements of the application to deliver high-performance as well. Since application software forms the basis of such designs, the need to tune the underlying SoC architecture for extracting maximum performance from the software code has become imperative. In this paper, we propose a framework that enables software development, verification and evaluation from the very beginning of MP-SoC design cycle. Unlike traditional SoC design flows where software design starts only after the initial SoC architecture is ready, our framework allows a co-development of the hardware and the software components in a tightly coupled loop where the hardware can be refined by considering the requirements of the software in a stepwise manner. The key element of this framework is the integration of a fine-grained software instrumentation tool into a system-level-design (SLD) environment to obtain accurate software performance and memory access statistics. The accuracy of such statistics is comparable to that obtained through instruction set simulation (ISS), while the execution speed of the instrumented software is almost an order of magnitude faster than ISS. Such a combined design approach assists system architects to optimize both the hardware and the software through fast exploration cycles, and can result in far shorter design cycles and high productivity. We demonstrate the generality and the efficiency of our methodology with two case studies selected from two most prominent and computationally intensive embedded application domains