Embedded processors are the heart of embedded systems. Reconfigurable embedded processors comprise an extended instruction set that is implemented using a reconfigurable fabric (similar to a field-programmable gate array, FPGA). This book presents novel concepts, strategies, and implementations to increase the run-time adaptivity of reconfigurable embedded processors. Concepts and techniques are presented in an accessible, yet rigorous context. A complex, realistic H.264 video encoder application with a high demand for adaptivity is presented and used as an example for motivation throughout the book. A novel, run-time system is demonstrated to exploit the potential for adaptivity and particular approaches/algorithms are presented to implement it.

Embedded processors are the heart of embedded systems. Reconfigurable embedded processors comprise an extended instruction set that is implemented using a reconfigurable fabric (similar to a field-programmable gate array, FPGA). This book presents novel concepts, strategies, and implementations to increase the run-time adaptivity of reconfigurable embedded processors. Concepts and techniques are presented in an accessible, yet rigorous context. A complex, realistic H.264 video encoder application with a high demand for adaptivity is presented and used as an example for motivation throughout the book. A novel, run-time system is demonstrated to exploit the potential for adaptivity and particular approaches/algorithms are presented to implement it.

This book constitutes the proceedings of the 34th International Conference on Architecture of Computing Systems, ARCS 2021, held virtually in July 2021. The 12 full papers in this volume were carefully reviewed and selected from 24 submissions. 2 workshop papers (VEFRE) are also included. ARCS has always been a conference attracting leading-edge research outcomes in Computer Architecture and Operating Systems, including a wide spectrum of topics ranging from fully integrated, self-powered embedded systems up to high-performance computing systems. It also provides a platform covering newly emerging and cross-cutting topics, such as autonomous and ubiquitous systems, reconfigurable computing and acceleration, neural networks and artificial intelligence. The selected papers cover a variety of topics from the ARCS core domains, including heterogeneous computing, memory optimizations, and organic computing.