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This is an implementation of http://arxiv.org/abs/1204.3425 "Exact diagonalization of the Hubbard model on graphics processing units" by Siro and Harju.

There are 2 programs: main and main2D. The former is for 1D Hubbard, the latter is for 2D Hubbard. Everything is split up in several classes to make reusing code easy: The Hamiltonian and HubHam2D classes build the full (dense) Hamiltonian Matrix. SparseHamiltonian stores the Hubbard Hamiltonian in parts: an spin up and a spin down part. The matrix themselves are storred in the ELL format. The SparseHamiltonian2D does the same but for 2D Hubbard. However, here we make a detour: we first store the matrices in the CRS format (the SparseHamiltonian2D_CSR class) and then convert it in the ELL format. The reason is that for ELL, we need to know the maximum number of non-zero elements (nnz) of a row.

There are several branches in the git repo: the master contains only the CPU version. The branch 'GPU' constains the GPU version and the branch 'PRIMME' used the PRIMME library to find the eigenvalues and eigenvectors. You can find PRIMME at http://www.cs.wm.edu/~andreas/software/