1 citations · 1 across the 2 of their papers we have counts for
4 papers
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…
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…