Quantum Espresso

Submitting Batch Jobs

The are the commands for ASE/python mode and the "native" (no ASE/python) mode:

esp-ver-bsub <version> myscript.py
esp-ver-bsub-native <version> -q suncat-test -o my.log -n 8 pw.x -in pw.inp

Dealing With Memory Issues (e.g. Swapping Jobs)

For a "typical" espresso job (default planewave parallelization):

• if a job swaps on suncat (24GB nodes), run it on suncat2 (48GB nodes)
• if a job swaps on suncat2 (48GB nodes), run it on suncat3 (64GB nodes)
• if a job swaps on suncat3, use 2 suncat3 nodes. suncat3 (only!) has a fast interconnect that should help them run reasonably well on multiple nodes

In the longer term we would like to have a memory estimator that will allow you to choose the best queue in advance, although posts on the espresso mailing list suggest this may be difficult.

k-point Parallelization

• NOTE: typically one does NOT do k-point parallelization for large systems. Only the gamma-point is necessary.
• k-point parallelization across nodes will not be as cpu-efficient as planewave parallelization within one node, so use it judiciously
• k-point parallelization is not as memory efficient as planewave parallelization, but it is supposed to scale better to more nodes (ask cpo if you want a better explanation). In particular, my understanding is that k-point parallelization will not reduce the memory usage per node.
• vossj and cpo have not yet seen good scaling behavior for the k-point parallelization for small systems (2x2x3 system). lausche has reported good k-point scaling for 3x3x4 systems. there have been some not-understood hangs with npool=3 or 4 (see below).
• to turn on k-point parallelization:
  • for ase mode: add parameter "parflags='-npool 2'" to the espresso object. This is a general-purpose string for passing run-time options to espresso executables.
  • for native mode: add something like "-npool 2" at the end of the line
• an example for 16 cores (2 nodes) and npool=2: each of the 2 pools of 8 cores would parallelize over planewaves, but the 2 pools would process pairs of k-points in parallel. If one had 9 k-points, they would get processed in pairs, but the last one would only be processed on one node, leaving the other idle, which is not ideal.
• if you have done it correctly, you should see a line about "K-points division" in your espresso log file (the planewave parallelization produces a line like "R & G space division")
• there is a chicken-and-egg problem: to run your job one needs to know the number of reduced k-points (to determine npool) however one has to run the job to learn what this number is. a workaround for this would be to run it first in the test queue to learn the reduced number of k-points.

Reducing Memory Usage for Large Systems

From http://www.democritos.it/pipermail/pw_forum/2008-January/008101.html

Excerpt (relevant for the "native" (non-ASE) mode):

• consider reducing the planewave cutoff, IF it won't affect your results too much

• is your system an isolated system? then use this keyword:

  K_POINTS gamma
  

  it will use k=0 only (which is all you need for an isolated system) and exploit various tricks to reduce memory usage

• setting option "diago_david_ndim" to the minimum (2) and "mixing_ndim" to a smaller value (4) reduces memory usage, but may increase CPU time
• using diagonalization='cg' will also reduce memory usage, but it will increase CPU time by a sizable amount
• do not calculate stress if you do not need to: it is expensive

In ASE-mode we are currently unable to set the "K_POINTS gamma" field and "diago_david_ndim". The other two can be specified with the convergence keyword. "mixing_ndim" is "mix", and "diagonalization" is "diag". For example:

convergence = {'energy':1e-6,
               'mixing':0.7,
               'maxsteps':100,
               'mix':4,
               'diag':'cg'},

Example Scripts

A simple optimization: esp.py
Calculate density-of-states: espdos.py
Plot density-of-states: espdosplot.py
NEB: espneb.py

Running in "native" mode (see esp-ver-bsub-native command above): pw.inp

Versions

SUNCAT Quantum Espresso Talks

Introduction/Usage (Johannes Voss): jvexternal.pdf

Accuracy (Jewe Wellendorff, Keld Lundgaard, NOTE: password protected because it contains VASP benchmark data): kelu.pdf

Speed/Convergence (AJ Medford): aj.pptx

Scaling behavior (Christopher O'Grady): espscaling.pptx

Private Espresso Builds

Copy this script, and then edit the appropriate lines at the top:

/afs/slac/g/suncat/share/scripts/privesp.csh

Avoid syntax error in Python run scripts

There is a simple trick to catch syntax errors even before submitting them to the test queue. Just wrap the ase submit command in the following function (e.g. via your bashrc) and a faulty python script will be exited with an error message without waiting in any queue.

    function esp(){    
        python -m py_compile ${1}
    if [ $? -ne 0 ]
    then
        echo "Not compiling"
        return 1
    fi
    chmod -v 755 $1
    esp-ver-bsub 18 $@
    }

  Espresso ASE To-Do List

• merge branch with espresso trunk
• become part of ASE svn (need to follow new ASE guidelines)
• dry-run mode to get memory estimate
• understand failing espresso tests
• record uspp and executable directory in output (and/or svn version, somehow?)
• neb (done)
• constraints interface to pass ASE constraints to espresso
• dos (done)
• bandgaps (done)
• separation of site-specific code from ASE code (including site-specific "scratch") (done)
• make beef errors accessible from ASE
• beef self-tests integrated with espresso self-tests
• support kpoint parallelization (done)
• look into other parallelization (openmp, scalapack)
• documentation/examples (including on ASE website)
• fix popen warnings on suncat3
• eliminate difference between batch/non-batch running
• how to get automatic python recompilation with setup.py build approach?
• can we eliminate os-dependent stuff, like grep/egrep/sed?
• eliminate need for calc.stop() with multiple calculations (done)
• get work function without dumping out the electrostatic cube file? (chuan has tools for this)
• dipole correction goes in the middle of unit cell by default (in python, chuan makes sure it goes in the biggest gap) (done)