×

The linked neighbour list (LNL) method for fast off-lattice Monte Carlo simulations of fluids. (English) Zbl 1333.82023

Summary: We present a new algorithm, called linked neighbour list (LNL), useful to substantially speed up off-lattice Monte Carlo simulations of fluids by avoiding the computation of the molecular energy before every attempted move. We introduce a few variants of the LNL method targeted to minimise memory footprint or augment memory coherence and cache utilisation. Additionally, we present a few algorithms which drastically accelerate neighbour finding. We test our methods on the simulation of a dense off-lattice Gay-Berne fluid subjected to periodic boundary conditions observing a speedup factor of about 2.5 with respect to a well-coded implementation based on a conventional link-cell. We provide several implementation details of the different key data structures and algorithms used in this work.

MSC:

82C80 Numerical methods of time-dependent statistical mechanics (MSC2010)
82D15 Statistical mechanics of liquids

Software:

DESMOND; IML++
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] (Binder, K., Application of Monte Carlo in Statistical Physics (1984), Springer-Verlag: Springer-Verlag Amsterdam) · Zbl 0564.65002
[2] Allen, M. P.; Tildesley, R. M., Computer Simulation of Liquids (1987), Clarendon Press: Clarendon Press Oxford · Zbl 0703.68099
[3] Frenkel, D.; Smith, B., Understanding Molecular Simulation: From Algorithms to Applications (1996), Academic Press: Academic Press San Diego · Zbl 0889.65132
[4] Panagiotopoulos, A. Z., Mol. Phys., 61, 813 (1987)
[5] Smit, B.; Karaborni, S.; Siepmann, J. I., J. Chem. Phys., 102, 2126 (1995)
[6] Pant, P. V.K.; Theodorou, D. N., Macromolecules, 28, 7224 (1995)
[7] Uhlherr, A.; Mavrantzas, V. G.; Doxastakis, M.; Theodorou, D. N., Macromolecules, 34, 8554 (2001)
[8] Baschnagel, J.; Binder, K.; Doruker, P.; Gusev, A. A.; Hahn, O.; Kremer, K.; Mattice, W. L.; Muller-Plathe, F.; Murat, M.; Paul, W.; Santos, S.; Suter, U. W.; Tries, V., Adv. Polym. Sci., 152, 41 (2000)
[9] Mavrantzas, V. G.; Boone, T. D.; Zervopoulou, E.; Theodorou, D. N., Macromolecules, 32, 5072 (1999)
[10] Metropolis, N., J. Chem. Phys., 21, 1087 (1953)
[11] Hockney, R. W.; Eastwood, J. W., Computer Simulations Using Particles (1981), McGraw-Hill: McGraw-Hill New York · Zbl 0662.76002
[12] Verlet, L., Phys. Chem., 46, 98 (1967)
[13] Sadus, R. J., Molecular Simulation of Fluids: Theory, Algorithms and Object-Orientation (1999), Elsevier
[14] Heinz, T. N.; Hünenberger, P. H., A fast pairlist-construction algorithm for molecular simulations under period boundary conditions, J. Comput. Chem., 25, 1474 (2004)
[15] Yao, Z.; Wang, J.-S.; Liu, G.-R.; Cheng, M., Comput. Phys. Commun., 161, 27 (2004)
[16] Pütz, M.; Kolb, A., Comput. Phys. Commun., 113, 145 (1998)
[17] Mattson, W.; Rice, B. M., Comput. Phys. Commun., 119, 135 (1999)
[18] Gonnet, P., J. Comput. Chem., 28, 570 (2007)
[19] Zara, S. J.; Nicholson, D., Mol. Simul., 5, 245 (1990)
[20] Gay, J. G.; Berne, B. J., J. Chem. Phys., 74, 3316 (1981)
[21] Berardi, R.; Fava, C.; Zannoni, C., Chem. Phys. Lett., 297, 462 (1995)
[22] (Pasini, P.; Zannoni, C., Advances in the Computer Simulations of Liquid Crystals (2000), Kluwer: Kluwer Dordrecht), 17-50
[23] J. Dongarra, A. Lumsdaine, X. Niu, R. Pozo, K. Remington, Sparse matrix libraries in C++ for high performance architectures, in: Proc. OON-SKI ’94; J. Dongarra, A. Lumsdaine, X. Niu, R. Pozo, K. Remington, Sparse matrix libraries in C++ for high performance architectures, in: Proc. OON-SKI ’94
[24] Kotakemori, H.; Hasegawa, H.; Kajiyama, T.; Nukada, A.; Suda, R.; Nishida, A., OpenMP Shared Memory Parallel Programming (2008), Springer, pp. 153-163
[25] P.S. Lomdahl, D.M. Beazley, Multi-million particle molecular dynamics on MPPs, in: Second International Workshop, PARA95, Lyngby, Denmark, 1995; P.S. Lomdahl, D.M. Beazley, Multi-million particle molecular dynamics on MPPs, in: Second International Workshop, PARA95, Lyngby, Denmark, 1995
[26] J.C. Phillips, G. Zheng, S. Kumar, L.V. Kalé, NAMD: Biomolecular simulation on thousands of processors, in: Proc. SC ’02; J.C. Phillips, G. Zheng, S. Kumar, L.V. Kalé, NAMD: Biomolecular simulation on thousands of processors, in: Proc. SC ’02
[27] Grest, G. S.; Dünweg, B.; Kremer, K., Comput. Phys. Commun., 55, 269 (1989)
[28] T.C. Germann, K. Kadau, P.S. Lombdahl, 25 Tflop/s multibillion-atom molecular dynamics simulations and visualisation/analysis on BlueGene/L, in: Proc. SC ’05; T.C. Germann, K. Kadau, P.S. Lombdahl, 25 Tflop/s multibillion-atom molecular dynamics simulations and visualisation/analysis on BlueGene/L, in: Proc. SC ’05 · Zbl 1156.82329
[29] De Fabritiis, G., Comput. Phys. Commun., 176, 660 (2007)
[30] K.J. Bowers, E. Chow, H. Xu, R.O. Dror, M.P. Eastwood, B.A. Gregersen, J.L. Klepeis, I. Kolossvary, M.A. Moraes, F.D. Sacerdoti, J.K. Salmon, Y. Shan, D.E. Shaw, Scalable algorithms for molecular dynamics simulations on commodity clusters, in: Proc. SC ’08; K.J. Bowers, E. Chow, H. Xu, R.O. Dror, M.P. Eastwood, B.A. Gregersen, J.L. Klepeis, I. Kolossvary, M.A. Moraes, F.D. Sacerdoti, J.K. Salmon, Y. Shan, D.E. Shaw, Scalable algorithms for molecular dynamics simulations on commodity clusters, in: Proc. SC ’08
[31] Rapaport, D. C., Comput. Phys. Commun., 174, 521 (2006)
[32] Anderson, J. A.; Lorenz, C. D.; Travesset, A., J. Comput. Phys., 227, 5342 (2008)
[33] Rapaport, D. C., Comput. Phys. Commun., 62, 271 (1991)
[34] Altmann, S. L., Rotations, Quaternions and Double Groups (1986), Dover Publications · Zbl 0683.20037
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.