While pure-play quantum computing (QC) gets most of the QC-related attention, there’s also been steady progress adapting quantum methods for select use on classical computers. World interest in Quantum Computing warms up the interest in Quantum-Inspired algorithms, among them Quantum Annealing Simulation(QA).
QA has nothing in common with qubits and сryocooler but offers a fast optimization method for complex but structured non-convex landscape.
Before moving further, we recommend you to read first about the Simulated Annealing because QA is a kind of extension of classical SA. Read here and here.
🦨Why not GPU? None of these accelerators are suitable for complete graphs where every node has an interaction with all the other nodes. It is very difficult to accelerate QMC algorithm for complete graphs using GPUs due to the lack of SIMD operations and high data dependency
🔗D-Wave Two -commercially available computer for QA simulation