High Performance Computing for Eigenvalue Solver in Density-Matrix Renormalization Group Method: Parallelization of the Hamiltonian Matrix-vector Multiplication
Susumu Yamada (CCSE, Japan Atomic Energy Agency)
Masahiko Okumura (CCSE, Japan Atomic Energy Agency)
Masahiko Machida (CCSE, Japan Atomic Energy Agency)
The Density Matrix Renormalization Group (DMRG) method is widely used by computational physicists as a high accuracy tool to obtain the ground state of large quantum lattice models. Since the DMRG method has been originally developed for 1-D models, many extended method to a 2-D model have been proposed. However, some of them have issues in term of their accuracy. It is expected that the accuracy of the DMRG method extended directly to 2-D models is excellent. The direct extension DMRG method demands an enormous memory space. Therefore, we parallelize the matrix-vector multiplication in iterative methods for solving the eigenvalue problem, which is the most time- and memory-consuming operation. We find that the parallel efficiency of the direct extension DMRG method shows a good one as the number of states kept increases.
Parallel and Distributed Computing, Numerical Algorithms for CS&E
Toulouse | France | 2008 | June | 24  25  26  27