Efficiency of linked cell algorithms
The linked cell algorithm is an essential part of molecular simulation software, both molecular dynamics and Monte Carlo. Though it scales linearly with the number of particles, there has been a constant interest in increasing its performance, because a large part of CPU time is spent to identify th...
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          | Published in | Computer physics communications Vol. 182; no. 3; pp. 611 - 615 | 
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| Main Authors | , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
            Elsevier B.V
    
        01.03.2011
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 0010-4655 1879-2944  | 
| DOI | 10.1016/j.cpc.2010.11.002 | 
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| Abstract | The linked cell algorithm is an essential part of molecular simulation software, both molecular dynamics and Monte Carlo. Though it scales linearly with the number of particles, there has been a constant interest in increasing its performance, because a large part of CPU time is spent to identify the interacting particles. Several recent publications proposed improvements to the algorithm and investigated their efficiency by applying them to particular setups. Here we develop a general method to evaluate the efficiency of these algorithms which is mostly independent of the parameters of the simulation, and test it for a number of linked cell algorithms. We also propose a combination of linked cell reordering and interaction sorting that performs well for a broad range of simulation setups. | 
    
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| AbstractList | The linked cell algorithm is an essential part of molecular simulation software, both molecular dynamics and Monte Carlo. Though it scales linearly with the number of particles, there has been a constant interest in increasing its performance, because a large part of CPU time is spent to identify the interacting particles. Several recent publications proposed improvements to the algorithm and investigated their efficiency by applying them to particular setups. Here we develop a general method to evaluate the efficiency of these algorithms which is mostly independent of the parameters of the simulation, and test it for a number of linked cell algorithms. We also propose a combination of linked cell reordering and interaction sorting that performs well for a broad range of simulation setups. | 
    
| Author | Welling, Ulrich Germano, Guido  | 
    
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| Cites_doi | 10.1063/1.475217 10.1016/0010-4655(90)90007-N 10.1016/j.jcp.2008.01.047 10.1007/s00778-005-0166-4 10.1002/(SICI)1096-987X(199703)18:4<478::AID-JCC3>3.0.CO;2-Q 10.1002/jcc.20071 10.1016/j.cpc.2007.05.009 10.1016/S0010-4655(98)00203-3 10.1063/1.463137 10.1016/j.cpc.2004.04.004 10.1002/jcc.10123 10.1063/1.2719690 10.1002/jcc.20267 10.1103/PhysRev.159.98 10.1016/S0010-4655(00)00050-3 10.1016/j.cpc.2005.03.110 10.1016/S0010-4655(98)00074-5 10.1021/j100303a004 10.1016/j.cpc.2008.05.008 10.1142/S0129183106010182 10.1016/0021-9991(73)90046-6 10.1063/1.442716 10.1016/j.molliq.2005.11.029 10.1016/0167-7977(88)90014-7 10.1016/j.cpc.2005.03.111 10.1006/jcph.1995.1039 10.1002/jcc.20563  | 
    
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| Keywords | Molecular simulation Linked cell list Monte Carlo Neighbour list Molecular dynamics Linked cell reordering Interaction sorting  | 
    
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| SubjectTerms | Algorithms Central processing units Computer programs Computer simulation Interaction sorting Linked cell list Linked cell reordering Mathematical models Molecular dynamics Molecular simulation Monte Carlo Monte Carlo methods Neighbour list Software  | 
    
| Title | Efficiency of linked cell algorithms | 
    
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