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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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giannozz 2012-10-12 13:01:12 +00:00
parent 536bfa19d3
commit 140f1e6ecf
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11
Doc/user_guide.tex
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@ -1449,9 +1449,10 @@ of processors of each pool.
\paragraph{Massively parallel calculations}
For very large jobs (i.e. O(1000) atoms or more) or for very long jobs,
to be run on massively parallel machines (e.g. IBM BlueGene) it is
crucial to use in an effective way all available parallelization levels. Without a judicious choice of
parameters, large jobs will find a stumbling block in either memory or
CPU requirements.
crucial to use in an effective way all available parallelization levels.
Without a judicious choice of parameters, large jobs will find a
stumbling block in either memory or CPU requirements. Note that I/O
may also become a limiting factor.
Since v.4.1, ScaLAPACK can be used to diagonalize block distributed
matrices, yielding better speed-up than the internal algorithms for
@ -1556,7 +1557,9 @@ You can use input variable \texttt{disk\_io='minimal'}, or even
into trouble (or into angry system managers) with excessive I/O with \pwx.
The code will store wavefunctions into RAM during the calculation.
Note however that this will increase your memory usage and may limit
or prevent restarting from interrupted runs.
or prevent restarting from interrupted runs. For very large runs,
you may also want to use \texttt{wf\_collect=.false.} and (CP only)
\texttt{saverho=.false.} to reduce I/O to the strict minimum.
\subsection{Tricks and problems}