Canonical Monte Carlo multispin cluster method

We present a new Canonical Multispin-flip Cluster Monte Carlo algorithm for Ising model and describe efficient implementations for hybrid supercomputer. Our method takes advantage of the computing architecture for parallel and multi-threaded operations and uses a sequential cluster state update scheme. Due to the peculiarity of the implementation, the method is more effective for models with a restricted radius of interaction. It is based on combining a random selection of spin cluster by the Monte Carlo method with a complete enumeration of the all states of the selected cluster. To show how it works we applied our method to models of interacting magnetic Ising-moments: ferromagnetic Ising model, the Edwards–Anderson spin glass model, dipolar spin ice on hexagonal and pentagonal Cairo lattices.