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Added remark on how to reduce I/O
git-svn-id: http://qeforge.qe-forge.org/svn/q-e/trunk/espresso@9529 c92efa57-630b-4861-b058-cf58834340f0
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@ -1449,9 +1449,10 @@ of processors of each pool.
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\paragraph{Massively parallel calculations}
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For very large jobs (i.e. O(1000) atoms or more) or for very long jobs,
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to be run on massively parallel machines (e.g. IBM BlueGene) it is
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crucial to use in an effective way all available parallelization levels. Without a judicious choice of
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parameters, large jobs will find a stumbling block in either memory or
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CPU requirements.
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crucial to use in an effective way all available parallelization levels.
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Without a judicious choice of parameters, large jobs will find a
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stumbling block in either memory or CPU requirements. Note that I/O
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may also become a limiting factor.
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Since v.4.1, ScaLAPACK can be used to diagonalize block distributed
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matrices, yielding better speed-up than the internal algorithms for
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@ -1556,7 +1557,9 @@ You can use input variable \texttt{disk\_io='minimal'}, or even
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into trouble (or into angry system managers) with excessive I/O with \pwx.
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The code will store wavefunctions into RAM during the calculation.
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Note however that this will increase your memory usage and may limit
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or prevent restarting from interrupted runs.
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or prevent restarting from interrupted runs. For very large runs,
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you may also want to use \texttt{wf\_collect=.false.} and (CP only)
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\texttt{saverho=.false.} to reduce I/O to the strict minimum.
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\subsection{Tricks and problems}
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