A Quantum Materials Path to Next-Generation Computing

Computing technology is the at the core of the information age forming the basis of all of millennium goals of United Nations. However, Computing is at a momentous point today as AI and big data drive massive demand for computational hardware, while historic Moore's law performance scaling is slowing down.<br/><br/>In this talk, I will outline a framework that combines the energy/dimension scaling (Moore’s law), computer error rates (Shannon computing) and modern AI architectures (drawing mainly from Nature Physics 14, no. 4 (2018): 338) , https://www.nature.com/articles/s41567-018-0101-4).<br/><br/><b><i>A room-temperature quantum materials path to next-generation computing:</i></b> Next, I describe a quantum and memory materials-centric approach to enable the computing for beyond the CMOS era. I will outline a number of pathways for computing devices that utilize quantum materials. I will generalize the search for the next computing device with a comprehensive list of quantum materials classes.<br/><br/>We will connect various required components of a computing system to the next generation materials. The materials and transductions are classified under switching, interconnects and detection and are tied to the required targets for materials performance. We also identify activity factor (i.e utilization of logic), memory BW wall (Turing wall) and thermal extraction as the near term limiting factors for computing. Finally, I describe potential ways to build generalized intelligence hardware overcoming interconnect, memory and compute bottlenecks.