Reproduce “Extreme-Scale Ising Machines with Cluster Mean-Field Theory” on OpenResearch
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About this paper
Xiuqi Zhang, Shuvro Chowdhury, Shaila Niazi, Christian Z. Pratt, Navid Anjum Aadit, Kerem Y. Camsari
CMFT partitions Ising graphs into hardware-sized clusters, updates spins locally in blocks and folds outside spins’ average values into effective biases. Cycling partitions changes which couplings are approximated at cluster boundaries. At L=160, four-cluster CMFT across four GPUs reached comparable energy densities to a full-graph run on one GPU, up to 15 times faster; ground-state energies were unknown.
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