Exact diagonalization of the Hubbard model on graphics processing units

Abstract We solve the Hubbard model with the exact diagonalization method on a graphics processing unit (GPU). We benchmark our GPU program against a sequential CPU code by using the Lanczos algorithm to solve the ground state energy in two cases: a one-dimensional ring and a two-dimensional square lattice. In the one-dimensional case, we obtain speedups of over 100 and 60 in single and double precision arithmetic, respectively. In the two-dimensional case, the corresponding speedups are over 110 and 70.

[1]  M. Gutzwiller Effect of Correlation on the Ferromagnetism of Transition Metals , 1963 .

[2]  Elliott H. Lieb,et al.  Absence of Mott Transition in an Exact Solution of the Short-Range, One-Band Model in One Dimension , 1968 .

[3]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[4]  Kiran Kumar Matam,et al.  GPU Accelerated Lanczos Algorithm with Applications , 2011, 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications.

[5]  Z. Meng,et al.  Quantum spin liquid emerging in two-dimensional correlated Dirac fermions , 2010, Nature.

[6]  Thomas E. Potok,et al.  Parallel latent semantic analysis using a graphics processing unit , 2009, GECCO '09.

[7]  J. Kanamori,et al.  Electron Correlation and Ferromagnetism of Transition Metals , 1963 .

[8]  J. Hubbard Electron correlations in narrow energy bands , 1963, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[9]  Michael Garland,et al.  Implementing sparse matrix-vector multiplication on throughput-oriented processors , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

[10]  Jack J. Purdum,et al.  C programming guide , 1983 .