Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
As processor architectures have increased their reliance on speculative execution to improve performance, the importance of accurate prediction of what to execute speculatively ha...
Polymorphous computer-based systems are systems in which the CPU architecture “morphs” or changes shape to meet the requirements of the application. Optimized and efficient de...
Brandon Eames, Ted Bapty, Ben Abbott, Sandeep Neem...
Customizing architectures for particular applications is a promising approach to yield highly energy-efficient designs for embedded systems. This work explores the benefits of arc...
Systems in the domain of high-performance video signal processing are becoming more and more programmable. We suggest an approach to design such systems that involves measuring, v...
Bart Kienhuis, Ed F. Deprettere, Kees A. Vissers, ...