Creating a Mass-Producible Ising Machine for Quantum-like Computing and Optimization at Room Temperature

Cristian Cassella

ECE Assistant Professor Cristian Cassella, in collaboration with Prof. Philip Feng from the University of Florida, has been awarded a $500K NSF grant on “Massive Scale Computing and Optimization through On-chip ParameTric Ising MAchines (OPTIMA)”. Through this support, the two investigators and their groups will aim to draw and demonstrate a new path towards quantum-like computing and optimization capabilities in components that can operate at room temperature and can be manufactured en-mass through processing steps frequently used to build the integrated circuits used by any commercial radios.

Abstract Source: NSF

For decades, academia and industry have relied on deterministic algorithms and on general-purpose von-Neumann computing architectures to solve combinatorial-optimization (CO) problems within natural and social sciences. As Moore’s law continues to slow down, the existing computing paradigm is reaching the limit of maximum complexity of the CO problems it can tackle, thus becoming increasingly inadequate to answer, in reasonable times, the fundamental questions that keep rising in a wide range of disciplines, spanning from engineering, physics and medicine to economics and finance. By emulating quantum systems, new computing architectures known as Ising Machines (IMs) have been emerging. IMs offer the unique opportunity to solve extraordinarily complex CO problems much faster than any existing von-Neumann counterparts. Yet, to date, no IM technology can afford a massive number of spins to handle the currently unsolvable CO problems, while ensuring a low-power consumption, a compact form factor, a chip-scale integration and a manufacturability en masse through the consolidated wafer-scale fabrication processes offered by the semiconductor industry. The goal of this project is to explore and develop a new IM, namely the first On-chip ParameTric Ising MAchine (OPTIMA). Thanks to its unique highly reprogrammable dynamics, triggered without requiring any special environmental conditions or any time-consuming pre-processing steps while exclusively requiring chip-scale components that can be monolithic integrated in favor of a massive scale production, the development of OPTIMA will pave the way towards powerful, fast and miniaturized quantum-inspired computing systems, accessible to everybody from everywhere. This will allow the creation of new cyber infrastructures that scholars, scientists, engineers and educators worldwide will be able to use in order to address relevant technological and social challenges. The project team is collaborating with STEM education and workforce development programs, at both Northeastern University and the University of Florida, to organize and host on-campus activities with students and teachers from both K-12 schools and community colleges, as well as outreach visits to local schools to encourage and broaden participation of underrepresented groups. The project achievements are enriching both the undergraduate and the graduate courses that the investigators teach on circuit theory, advanced acoustic-based technologies for communication and sensing, micro/nanoelectromechanical systems (MEMS/NEMS), and quantum engineering devices and systems.

OPTIMA is leveraging the unique dynamical features governing the electrical response of a synchronized network of coupled on-chip Electro-Acoustic-Parametric-Oscillators (EAPOs) exploiting the uniquely combined ferroelectric and acoustic properties of Aluminum Scandium Nitride (AlScN) micro/nano devices to create extraordinarily low-power and highly miniaturized artificial spins, manufacturable through complementary-metal-oxide-semiconductor (CMOS) processes. Such unique features allow the breaking of all the previous paradigms in the design of IMs by simultaneously enabling >106 spins, a CMOS-compatible wafer-scale manufacturing and room-temperature operation while consuming less than 1 Watt. Further, thanks to its highly parallelized computational flow and because the EAPOs are operating in the Super-High-Frequency (SHF) range, OPTIMA is able to solve even the hardest nondeterministic polynomial time (NP) CO problems in nanosecond time scales, independently of the problem size. Finally, since OPTIMA is manufacturable through CMOS compatible processes, it is greatly leveraging conventional IC components built on the same silicon wafer to enable flexible programming, based on the CO problems of interest, as well as compact read-out schemes.

Related Faculty: Cristian Cassella

Related Departments:Electrical & Computer Engineering