5 papers
Accelerating Hybrid XORCNF Boolean Satisfiability Problems Natively with In-Memory Computing
Haesol Im, Fabian Böhm, Giacomo Pedretti +14
The Boolean satisfiability (SAT) problem is a computationally challenging decision problem central to many industrial applications. For SAT problems in cryptanalysis, circuit desig…
A Statistical Analysis for Per-Instance Evaluation of Stochastic Optimizers: Avoiding Unreliable Conclusions
Moslem Noori, Elisabetta Valiante, Thomas Van Vaerenbergh +2
A key trait of stochastic optimizers is that multiple runs of the same optimizer in attempting to solve the same problem can produce different results. As a result, their performan…
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…
Performance of QUBO-Formulated MIMO Detection Under Hardware Precision Constraints
Seyedkhashayar Hashemi, Elisabetta Valiante, Ignacio Rozada +1
The evolution of multiple-input, multiple-output (MIMO) systems requires the efficient detection algorithms to overcome the exponential computational complexity of optimal maximum…
Parallel Tempering-Inspired Distributed Binary Optimization with In-Memory Computing
Xiangyi Zhang, Fabian Böhm, Fabian Böhm +8
In-memory computing (IMC) has been shown to be a promising approach for solving binary optimization problems while significantly reducing energy and latency. Building on the advant…