In embedded systems, modeling the performance of off-the-shelf processors is very important to enable the designer to estimate the capability of each candidate processor against the target application. Considering the large number of available embedded processors, the need has increased for building an infrastructure by which it is possible to estimate the performance of a given application on a certain processor with a minimum of time and resources. This paper presents the use a Xilinx MicroBlaze softcore processor as a reference model augmented by FPGA-based profiling mechanism to extract the functional statistics that characterize the target application. Linear regression analysis is implemented for mapping the application functional behavior on the reference model (MicroBlaze) to the performance of the candidate processors.
Fadi Obeidat is currently a Silicon Architect at Intel Corporation. His research interests include Embedded Systems Design, Performance Modeling and Engineering Education. He received his B.S., M.S. and Ph.D. degrees in Computer Engineering from Jordan University of Science and Technology (JUST), Yarmouk University, and Virginia Commonwealth University (VCU) respectively. As a research assistant at the Unmanned Aerial Vehicles (UAVs) lab at VCU, he developed a Control Augmentation System (CAS) and integrated it to an existed autonomous Flight Control System (FCS) for UAVs - Funded by NASA. Dr. Obeidat joined Intel back in 2010 as an Emulation Architect. He has multiple proceedings in the following conferences: Annual ASEE Conference, IEEE-MSE, ACM/SIGDA FPGA, ESA and ERSA. Dr. Obeidat has served promoting engineering education through multiple programs such as the Virginia-North Carolina Louis Stock Alliance for Minority Participation (VA-NC LSAMP) at VCU -Funded by National Science Foundation (NSF), and the Intel “stay with it” program for STEM education.
Robert H. Klenke is currently an Associate Professor of Electrical Engineering at the Virginia Commonwealth University. His research interests include system level modeling, hardware description languages, and unmanned aerial vehicle (UAV) flight control systems and applications. Dr. Klenke received his B.S. degree in Electrical Engineering from the Virginia Military Institute in 1982, and his M.S. and Ph.D. Degrees in Electrical Engineering from the University of Virginia in 1989 and 1993, respectively. He is a senior member of the IEEE and a member of the IEEE Computer Society, Tau Beta Pi, and Eta Kappa Nu.