ABSTRACT Title of dissertation: MODELING AND MAPPING OF OPTIMIZED SCHEDULES FOR EMBEDDED SIGNAL PROCESSING SYSTEMS

The demand for Digital Signal Processing (DSP) in embedded systems has been increasing rapidly due to the proliferation of multimedia- and communication-intensive devices such as pervasive tablets and smart phones. Efficient implementation of em-bedded DSP systems requires integration of diverse hardware and software components, as well as dynamic workload distribution across heterogeneous computational resources. The former implies increased complexity of application modeling and analysis, but also brings enhanced potential for achieving improved energy consumption, cost or perfor-mance. The latter results from the increased use of dynamic behavior in embedded DSP applications. Furthermore, parallel programming is highly relevant in many embedded DSP areas due to the development and use of Multiprocessor System-On-Chip (MPSoC) technology. The need for efficient cooperation among different devices supporting di-verse parallel embedded computations motivates high-level modeling that expresses dy-namic signal processing behaviors and supports efficient task scheduling and hardware mapping. Starting with dynamic modeling, this thesis develops a systematic design method