22 citations · 59 across the 8 of their papers we have counts for
8 papers
Hardware-Compatible Single-Shot Feasible-Space Heuristics for Solving the Quadratic Assignment Problem
Haesol Im, Chan-Woo Yang, Moslem Noori +10
Research into the development of special-purpose computing architectures designed to solve quadratic unconstrained binary optimization (QUBO) problems has flourished in recent year…
Solving Boolean satisfiability problems with resistive content addressable memories
Giacomo Pedretti, Fabian Böhm, Tinish Bhattacharya +15
Solving optimization problems is a highly demanding workload requiring high-performance computing systems. Optimization solvers are usually difficult to parallelize in conventional…
Roadmap to Neuromorphic Computing with Emerging Technologies
Adnan Mehonic, Daniele Ielmini, Kaushik Roy +50
The roadmap is organized into several thematic sections, outlining current computing challenges, discussing the neuromorphic computing approach, analyzing mature and currently util…
Quantized Context Based LIF Neurons for Recurrent Spiking Neural Networks in 45nm
Sai Sukruth Bezugam, Yihao Wu, JaeBum Yoo +2
In this study, we propose the first hardware implementation of a context-based recurrent spiking neural network (RSNN) emphasizing on integrating dual information streams within th…
Energy landscapes of combinatorial optimization in Ising machines
Dmitrii Dobrynin, Adrien Renaudineau, Mohammad Hizzani +3
Physics-based Ising machines (IM) have been developed as dedicated processors for solving hard combinatorial optimization problems with higher speed and better energy efficiency. G…
Computing High-Degree Polynomial Gradients in Memory
T. Bhattacharya, G. H. Hutchinson, G. Pedretti +6
Specialized function gradient computing hardware could greatly improve the performance of state-of-the-art optimization algorithms, e.g., based on gradient descent or conjugate gra…
FPIA: Field-Programmable Ising Arrays with In-Memory Computing
George Higgins Hutchinson, Ethan Sifferman, Tinish Bhattacharya +1
Ising Machine is a promising computing approach for solving combinatorial optimization problems. It is naturally suited for energy-saving and compact in-memory computing implementa…
Memristor-based hardware and algorithms for higher-order Hopfield optimization solver outperforming quadratic Ising machines
Mohammad Hizzani, Arne Heittmann, George Hutchinson +6
Ising solvers offer a promising physics-based approach to tackle the challenging class of combinatorial optimization problems. However, typical solvers operate in a quadratic energ…