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-===== High-performance simulation of large bimolecular systems - NAMD =====
-NAMD, recipient of a 2002 Gordon Bell Award, is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD is file-compatible with AMBER, CHARMM, and X-PLOR and is distributed free of charge with source code.
-Documentation and source code on the web page of "[[http://www.ks.uiuc.edu/Research/namd/|Theoretical and computational biophysics group]]"
-There are few possibilities to start NAMD simulation on the MOGON cluster.
-//<PATH TO NAMD INSTALLATION>/namd2 <input configuration file>//
-This starts one threaded simulation direkt on the login host. Input configuration file describes simulation. Complete description of the input file format is available in the [[http://www.ks.uiuc.edu/Research/namd/2.9/ug/node9.html|NAMD Documentation]].
-Using threaded start allows to achieve performance increasing:
-//bsub -R "affinity[core(<number of cores>)]" <PATH TO NAMD INSTALLATION>/namd2 +p<number of threads> <input configuration file>//
-where <number of threads> is normally equal to <number of cores>.
-For example
-//bsub -R "affinity[core(16)]" <PATH TO NAMD INSTALLATION>/namd2 +p 16 <input configuration file>//
-starts NAMD simulation with 16 threads using 16 cores of a node.
-Mogon cluster contains different nodes with up to 64 cores.
-On machines with more than 32 cores it may be necessary to add a communication thread and run on one fewer core than the machine has.  For example on a 64-core machine this would be run as
-//bsub -R "affinity[core(64)]" <PATH TO NAMD INSTALLATION>/namd2 +p 63 +commthread <input configuration file>//
-=== Memory Usage ===
-NAMD has traditionally used less than 100MB of memory even for systems
-of 100,000 atoms.  With the reintroduction of pairlists in NAMD 2.5, however, memory usage for a 100,000 atom system with a 12A cutoff can approach 300MB, and will grow with the cube of the cutoff.  This extra memory is distributed across processors during a parallel run, but a single workstation may run out of physical memory with a large system.