The reconfiguration capabilities of FPGAs give the designers extended flexibility in terms of hardware maintainability. FPGAs can change the hardware functionalities mapped on them by taking the application offline, downloading a new configuration on the FPGA (and possibly new software for the processor, if any) and rebooting the system. Reconfiguration in this case is a process independent of the execution of the application. A different approach is the one that considers reconfiguration of the FPGA as part of the application itself, giving it the capability of adapting the hardware configured on the chip resources according to the needs of a particular situation during the execution time. In this case we are referring to this reconfiguration as dynamic reconfiguration and the reconfiguration process is seen as part of the application execution, and not as a stage prior to it. This module illustrates a particular technique, which is extending the previous two, that has been viable for most recent FPGA devices, Partial Dynamic Reconfiguration. To fully understand what this technique is, the concepts of reconfigurable computing, static and dynamic reconfiguration, and the taxonomy of dynamic reconfiguration itself must be analyzed. In this way partial dynamic reconfiguration can be correctly placed in the set of system development techniques that it is possible to implement on a modern FPGA chip.

After presenting different solutions proposed to design and implement dynamic reconfigurable systems, this module will describe a general and complete design methodology that can be followed as a guideline for designing reconfigurable computing systems. To design and implement a reconfigurable computing system, designers need Computer-Aided Design (CAD) tools for system design and implementation, such as a design analysis tool for architecture design, a synthesis tool for hardware construction, a simulator for hardware behavior simulation, and a placement and routing tool for circuit layout. We may build these tools ourselves or we can also use commercial tools and platforms for reconfigurable system design. The first choice implies a considerable investment in terms of both time and effort to build a specific and optimized solution for the given problem, while the second one allows the re-use of knowledge, cores, and software to reach a good solution to the same problem more rapidly. This module is guiding the students through an historical view on how CAD frameworks evolved through the years. This is done to show how fast the technology is evolving and the rationale behind the choice made to improve the users experience when working with an FPGA-based system. Not only commercial tools are described, but also the personal journey done by the course instructor and his research team, starting from his early days as a PhD up to the research challenges they are nowadays working on.

We are working at the edge of the research in the area of reconfigurable computing. FPGA technologies are not used only as standalone solutions/platforms but are now included into cloud infrastructures. They are now used both to accelerate infrastructure/backend computations and exposed as-a-Service that can be used by anyone. Within this context we are facing the definition of new research opportunities and technologies improvements and the time cannot be better under this perspective. What it is needed now is new platform creation tools, monitoring and profiling infrastructure, better runtime management systems, static and dynamic workload partitioning, just to name a few possible areas of research. This module is concluding this course but posing interesting questions towards possible future research directions that may also point the students to other Coursera courses on FPGAs.