ASCENT: Ferroelectric-based Compute-in-Memory Dynamical Engine (Ferro-CoDE) to Solve Hard Combinatorial Optimization

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Not all computing problems are created equal. At the heart of many, increasingly important, applications ranging from the design of intelligent machines that can explain their decisions, to electronic design automation for tamper-proof integrated circuits, lies a class of combinatorial optimization problems that remain an unconquered bastion of traditional digital computing. As a case in point, solving the archetypal Boolean satisfiability problem, integral to many such applications, requires exponentially increasing energy and computation time that makes its practical deployment at large scales unfeasible. The proposed research aims to address this challenge through a cohesive across-the-stack effort that spans from the formulation of a physics-inspired computational model to designing a supporting hardware ecosystem that encompasses novel engineered materials and devices, circuits, and their subsequent system integration. The foundational principle of the Ferroelectric-based Compute-in-Memory Dynamical Engine (FerroCoDE) is based on exploiting the inherent efficiency of physical phenomena in nature (namely, maximization of entropy production) by creating unique synergies between physics and computation. To execute these computational models efficiently, the team of researchers is developing a new hardware platform that converges the unique capabilities of dynamical systems with compute-in-memory architectures, enabled through fundamental innovation in ferroelectric materials and their device functionalities. The FerroCoDE platform will enable orders-of-magnitude improvement in computational efficiency enabling the deployment of relevant applications at a scale and in (energy-constrained) environments that are presently challenging to achieve using present day computers. Furthermore, to broaden the impact of this work, the team will develop a publicly accessible online platform, OscWorks, for applying oscillator-based computing in education and research. Additionally, the team will engage with K-12 and undergraduate students through various initiatives such as workshops, online seminars, and research opportunities.The systems challenge that is being addressed by this ASCENT project is to design, fabricate and demonstrate a Ferroelectric Hafnium Oxide (HfO2) based Compute-in-Memory (CiM) Dynamical Engine (FerroCoDE) that leverages the rich non-linear analog dynamics of oscillators in conjunction with the area and energy efficiency of ferroelectric CiM architecture to accelerate the computationally hard maximum satisfiability problem. The FerroCoDE exploits a novel formulation of the satisfiability problem as the direct maximization of entropy in the compute engine which is being developed through a vertically integrated materials-to-systems effort that focusses on: (i) Development of phase- and crystallographic-texture-engineered HfO2-based ultra-thin ferroelectric and antiferroelectric films with tunable properties; (ii) Design and fabrication of a novel non-volatile 1FeFET-1FTJ memory cell and array to enable in-memory programming and evaluation of the satisfiability clauses; and energy efficient AFE oscillator arrays (iii) Building synergistic convergence between the hardware and algorithm; (iv) System engineering, with emphasis on developing learning algorithms to optimize dynamical system initialization, development of annealing schedules and hardware scalability. (v) Development and demonstration of a FerroCoDE prototype on PCB.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.