Approximate computing is an aggressive design technique aimed at achieving significant energy savings by trading off computational precision and accuracy in inherently error-tolerant applications. This introduces a new notion of quality as a fundamental design parameter. While ad-hoc solutions have been explored at various levels, systematic design approaches are lacking.
In future computing systems, such as the Internet-of-Things (IoT), functionality is increasingly defined by the networked connectivity of spatially distributed devices. This, however, poses fundamentally new design challenges and tradeoffs. Computation and communication need to be tightly coupled and jointly explored, e.g. to determine whether a functionality should be performed locally or remotely over the network in order to achieve the best performance and energy consumption.
Cyber-Physical Systems (CPS) promise great advances to society in fields such as transportation and healthcare. CPS are computer systems that interact directly with the physical world, such as in robotics or self-driving cars.
The challenge, according to WNCG Prof. Andreas Gerstlauer, is these systems must operate within tight constraints imposed by their physical environment. They must be able to complete tasks on time and with minimal overhead in a real-world environment.