Abstract Combinatorial optimization (CO) underpins critical applications in science and engineering, ranging from logistics to electronic design automation. A classic example of CO is the NP-complete Traveling Salesman Problem (TSP). Finding exact solutions for large-scale TSP instances remains computationally intractable; on von Neumann architectures, such solvers are constrained by the memory wall, incurring compute-memory traffic that grows with instance size. Metaheuristics, such as simulate
LIMO: Low-power in-memory-annealer and matrix-multiplication primitive for edge computing
Amod Holla·Kaushik Roy·Fernando Garcia-Redondo·Sutanu Sen·Sumedh Chatterjee·Francesca Iacopi·Dwaipayan Biswas·Anish Mukherjee
