3 papers
cs.AR2026
Energy-Efficient p-Bit-Based Fully-Connected Quantum-Inspired Simulated Annealer with Dual BRAM Architecture
Naoya Onizawa, Taiga Kubuta, Duckgyu Shin +1
Probabilistic bits (p-bits) offer an energy-efficient hardware abstraction for stochastic optimization; however, existing p-bit-based simulated annealing accelerators suffer from p…
cs.AR2026
Memory-Efficient FPGA Implementation of Stochastic Simulated Annealing
Duckgyu Shin, Naoya Onizawa, Warren J. Gross +1
Simulated annealing (SA) is a well-known algorithm for solving combinatorial optimization problems. However, the computation time of SA increases rapidly, as the size of the proble…
math.OC2026
Fast Solving Complete 2000-Node Optimization Using Stochastic-Computing Simulated Annealing
Kota Katsuki, Duckgyu Shin, Naoya Onizawa +1
In this paper, we evaluate stochastic-computing simulated annealing (SC-SA) for solving large-scale combinatorial optimization problems. SC-SA is designed using stochastic computin…