0398455 - ÚOCHB 2014 RIV NL eng J - Článek v odborném periodiku
Klemsa, Jakub - Řezáč, Jan
Parallel low-memory quasi-Newton optimization algorithm for molecular structure.
Chemical Physics Letters. Roč. 584, Oct 1 (2013), s. 10-13. ISSN 0009-2614. E-ISSN 1873-4448
Grant CEP: GA ČR GP13-01214P
Institucionální podpora: RVO:61388963
Klíčová slova: geometry optimization * parallelization * molecular graph
Kód oboru RIV: CF - Fyzikální chemie a teoretická chemie
Impakt faktor: 1.991, rok: 2013

We present a novel parallel gradient optimization algorithm designed for the optimization of molecular geometry - the parallel preconditioned LBFGS (PP-LBFGS) method. In each step, several additional gradient calculations (performed in parallel with the calculation of the potential) are used to improve the most important elements of the Hessian. The sparsity of the connectivity matrix and the graph theory are used to estimate multiple Hessian elements from each additional gradient calculation. The simplest variant of the algorithm, which requires 4 gradient evaluations per cycle, converges 2x-4x faster than the LBFGS algorithm, depending on the size of the system.
Trvalý link: http://hdl.handle.net/11104/0225938