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MacroModel Reference Manual - ISP

MacroModel Reference Manual - ISP

MacroModel Reference Manual - ISP

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Chapter 2: Running <strong>MacroModel</strong>file’s continued existence. When it fails to find the .slp file, it resumes execution. Thus, toresume execution of the <strong>MacroModel</strong> job, remove the .slp file using the UNIX rm command.The UNIX kill command can also be used to stop a <strong>MacroModel</strong> process; to stop the process,type:kill -STOP pidTo restart it later, type:kill -CONT pidwhere pid is the process identification number of the job.When a job is put to sleep the CPU suspends execution and the job may in time be swapped outof active memory (RAM); however, it continues to occupy swap space on disk. If, in a particularsituation, the availability of swap space is limiting the number of jobs that can be simultaneouslyrun, putting one or more of them to sleep will not help. This option is, however, usefulfor obtaining more responsive performance when CPU availability, rather than swap space, islimiting. There are less drastic means of lowering the priority of a job as well—namely,renice and npri—but these require special privileges if it is desired to restore the originalpriority.2.2.1.3 Triggering an Interim Job SummaryIf the program detects a file whose name is filename.upt, it will, at the next convenient point,print to the log file a summary of its progress so far, then remove the .upt file. In the currentversion of <strong>MacroModel</strong>, this facility is implemented only for conformational search. IfMaestro is running, the update information also appears in the Monitor panel. When Macro-Model is run as a standalone process, the user can trigger an update manually by simplycreating the .upt file.2.3 Network-Distributed ProcessingSome types of <strong>MacroModel</strong> calculations may be split into largely independent tasks which arerun separately on different processors or computers across a network. The number of tasks maybe greater than or equal to the number of processors requested, so that processors carry outmore than one task before the job finishes. Distributing the overall calculations across multipleprocessors (a form of parallel processing) can significantly reduce the time required tocomplete the job.<strong>MacroModel</strong> 9.7 <strong>Reference</strong> <strong>Manual</strong> 19

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