Reconfigurable MPSoC versus GPU: Performance, power and energy evaluation

Different characteristics of algorithms, perform better or worse on various target hardware. The consequent of this is, that the selection of one suitable hardware, such as Graphic Processing Units (GPU), Field Programmable Gate Arrays (FPGAs) or traditional processor cores is a challenging task for developers. The challenge is to choose the most suitable platform satisfying the requirements of the given application, such as real-time and power- / energy consumption constraints. Due to short time to market pressure, a fast development cycle is also a very important characteristic in industrial applications. This work evaluates the performance, power- /energy consumption and the development effort for three processor-based systems: an FPGA-based multiprocessor platform called RAMPSoC, a GPU and a CPU. Two real-world applications have been selected for this evaluation: 3D Ultrasound Computer Tomography and Object Recognition. The paper presents the realization of the applications on the different target hardware and discusses the results of the power and performance evaluation.