User Guide

user_guide

User Manual:

Open the PDF directly: View PDF .
Page Count: 27

PWscf User’s Guide (v.6.3)

(only partially updated)

Contents

1 Introduction 1

1.1 What can PWscf do.................................. 1

1.2 People ......................................... 2

1.3 Termsofuse...................................... 3

2 Compilation 4

3 Using PWscf 6

3.1 Inputdata....................................... 6

3.2 Dataﬁles ....................................... 7

3.3 Electronic structure calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.4 Optimization and dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

3.5 Direct interface with CASINO ............................. 10

3.6 Socketinterfacewithi-PI............................... 12

4 Performances 13

4.1 Executiontime .................................... 13

4.2 Memoryrequirements................................. 14

4.3 Filespacerequirements................................ 14

4.4 Parallelizationissues ................................. 15

4.5 Understanding the time report . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.5.1 Serialexecution................................ 16

4.5.2 Parallelexecution............................... 17

4.6 Restarting....................................... 18

4.6.1 Signal trapping (experimental!) . . . . . . . . . . . . . . . . . . . . . . . 19

5 Troubleshooting 19

5.1 Compilation problems with PLUMED ......................... 26

1 Introduction

This guide covers the usage of the PWscf (Plane-Wave Self-Consistent Field) package, a core

component of the Quantum ESPRESSO distribution. Further documentation, beyond what

is provided in this guide, can be found in the directory PW/Doc/, containing a copy of this guide.

Important notice: due to the lack of time and of manpower, this manual is only partially

updated and may contain outdated information.

This guide assumes that you know the physics that PWscf describes and the methods it

implements. It also assumes that you have already installed, or know how to install, Quantum

ESPRESSO. If not, please read the general User’s Guide for Quantum ESPRESSO, found

in directory Doc/ two levels above the one containing this guide; or consult the web site:

http://www.quantum-espresso.org.

People who want to modify or contribute to PWscf should read the Developer Manual:

Doc/developer man.pdf.

1.1 What can PWscf do

PWscf performs many diﬀerent kinds of self-consistent calculations of electronic-structure prop-

erties within Density-Functional Theory (DFT), using a Plane-Wave (PW) basis set and pseu-

dopotentials (PP). In particular:

•ground-state energy and one-electron (Kohn-Sham) orbitals, atomic forces, stresses;

•structural optimization, also with variable cell;

•molecular dynamics on the Born-Oppenheimer surface, also with variable cell;

•macroscopic polarization and ﬁnite electric ﬁelds via the modern theory of polarization

(Berry Phases);

•modern theory of orbital magnetization;

•free-energy surface calculation at ﬁxed cell through meta-dynamics, if patched with

PLUMED.

All of the above works for both insulators and metals, in any crystal structure, for many

exchange-correlation (XC) functionals (including spin polarization, DFT+U, meta-GGA, non-

local and hybrid functionals), for norm-conserving (Hamann-Schluter-Chiang) PPs (NCPPs) in

separable form or Ultrasoft (Vanderbilt) PPs (USPPs) or Projector Augmented Waves (PAW)

method. Noncollinear magnetism and spin-orbit interactions are also implemented. An im-

plementation of ﬁnite electric ﬁelds with a sawtooth potential in a supercell is also available.

Please note that NEB calculations are no longer performed by pw.x, but are instead carried out

by neb.x (see main user guide), a dedicated code for path optimization which can use PWscf

as computational engine.

1.2 People

The PWscf package (which in earlier releases included PHonon and PostProc) was originally

developed by Stefano Baroni, Stefano de Gironcoli, Andrea Dal Corso (SISSA), Paolo Giannozzi

(Univ. Udine), and many others. We quote in particular:

•David Vanderbilt’s group at Rutgers for Berry’s phase calculations;

•Paolo Umari (Univ. Padua) for ﬁnite electric ﬁelds;

•Ralph Gebauer (ICTP, Trieste) and Adriano Mosca Conte (SISSA, Trieste) for non-

collinear magnetism;

•Andrea Dal Corso for spin-orbit interactions;

•Carlo Sbraccia (Princeton) for improvements to structural optimization and to many

other parts;

•Dario Alf`e (University College London) for implementation of Born-Oppenheimer molec-

ular dynamics;

•Renata Wentzcovitch and collaborators (Univ. Minnesota) for variable-cell molecular

dynamics;

•Lorenzo Paulatto (Univ.Paris VI) for PAW implementation, built upon previous work by

Guido Fratesi (Univ.Milano Bicocca) and Riccardo Mazzarello (ETHZ-USI Lugano);

•Matteo Cococcioni (Univ. Minnesota) for DFT+U implementation;

•Timo Thonhauser (WFU) for vdW-DF, svdW-DF, and variants;

and the more recent contributors:

•Miha Gunde for interface with Grimme’s DFT-D3 code, as repackaged by Blint Aradi

•Pietro Bonf`a (CINECA) for memory estimator;

•Michele Ceriotti and Riccardo Petraglia (EPFL Lausanne) for interfacing with i-PI;

•Taylor Barnes (LBL) and Nicola Varini (CSCS) for improvements to hybrid functionals;

•Robert DiStasio (Cornell), Biswajit Santra (Princeton), Hsin-Yu Ko (Princeton), Thomas

Markovich (Harvard) for Tkatchenko-Scheﬄer stress in PWscf;

•Jong-Won Song (RIKEN) for Gau-PBE functional;

•Alberto Otero de la Roza (Merced Univ.) for XDM (exchange-hole dipole moment) model

of dispersions, PW86 (unrevised) and B86B functionals;

•Hannu-Pekka Komsa (CSEA/Lausanne) for the HSE functional;

•Gabriele Sclauzero (IRRMA Lausanne) for DFT+U with on-site occupations obtained

from pseudopotential projectors;

•Alexander Smogunov (CEA) for DFT+U with noncollinear magnetization and for calcu-

lation of Magnetic Anisotropy Energy using the Force Theorem;

•Burak Himmetoglou (UCSB) for DFT+U+J;

•Xiaochuan Ge (SISSA) for Smart MonteCarlo Langevin dynamics;

•Andrei Malashevich (Univ. Berkeley) for calculation of orbital magnetization;

•Minoru Otani (AIST), Yoshio Miura (Tohoku U.), Nicephore Bonet (MIT), Nicola Marzari

(Univ. Oxford), Brandon Wood (LLNL), Tadashi Ogitsu (LLNL), for ESM, Eﬀective

Screening Method (PRB 73, 115407 [2006]);

•Dario Alf`e, Mike Towler (University College London), Norbert Nemec (U.Cambridge) for

the interface with CASINO.

This guide was mostly written by Paolo Giannozzi. Mike Towler wrote the PWscf to CASINO

subsection. Michele Ceriotti and Riccardo Petraglia wrote the subsection on i-PI interface.

1.3 Terms of use

Quantum ESPRESSO is free software, released under the GNU General Public License.

See http://www.gnu.org/licenses/old-licenses/gpl-2.0.txt, or the ﬁle License in the

distribution).

We shall greatly appreciate if scientiﬁc work done using the Quantum ESPRESSO dis-

tribution will contain an acknowledgment to the following references:

P. Giannozzi, S. Baroni, N. Bonini, M. Calandra, R. Car, C. Cavazzoni, D. Ceresoli,

G. L. Chiarotti, M. Cococcioni, I. Dabo, A. Dal Corso, S. Fabris, G. Fratesi, S. de

Gironcoli, R. Gebauer, U. Gerstmann, C. Gougoussis, A. Kokalj, M. Lazzeri, L.

Martin-Samos, N. Marzari, F. Mauri, R. Mazzarello, S. Paolini, A. Pasquarello, L.

Paulatto, C. Sbraccia, S. Scandolo, G. Sclauzero, A. P. Seitsonen, A. Smogunov, P.

Umari, R. M. Wentzcovitch, J.Phys.: Condens.Matter 21, 395502 (2009)

and

P. Giannozzi, O. Andreussi, T. Brumme, O. Bunau, M. Buongiorno Nardelli, M.

Calandra, R. Car, C. Cavazzoni, D. Ceresoli, M. Cococcioni, N. Colonna, I. Carn-

imeo, A. Dal Corso, S. de Gironcoli, P. Delugas, R. A. DiStasio Jr, A. Ferretti, A.

Floris, G. Fratesi, G. Fugallo, R. Gebauer, U. Gerstmann, F. Giustino, T. Gorni, J

Jia, M. Kawamura, H.-Y. Ko, A. Kokalj, E. K¨u¸c¨ukbenli, M .Lazzeri, M. Marsili, N.

Marzari, F. Mauri, N. L. Nguyen, H.-V. Nguyen, A. Otero-de-la-Roza, L. Paulatto,

S. Ponc´e, D. Rocca, R. Sabatini, B. Santra, M. Schlipf, A. P. Seitsonen, A. Smo-

gunov, I. Timrov, T. Thonhauser, P. Umari, N. Vast, X. Wu, S. Baroni J.Phys.:

Condens.Matter 29, 465901 (2017)

Note the form Quantum ESPRESSO for textual citations of the code. Please also see

package-speciﬁc documentation for further recommended citations. Pseudopotentials should

be cited as (for instance)

[ ] We used the pseudopotentials C.pbe-rrjkus.UPF and O.pbe-vbc.UPF from

http://www.quantum-espresso.org.

References for all exchange-correlation functionals can be found in the header of ﬁle Modules/funct.f90.

2 Compilation

PWscf is included in the core Quantum ESPRESSO distribution. Instruction on how to in-

stall it can be found in the general documentation (User’s Guide) for Quantum ESPRESSO.

Typing make pw from the main Quantum ESPRESSO directory or make from the PW/

subdirectory produces the pw.x executable in PW/src and a link to the bin/ directory. In

addition, several utility programs, and related links in bin/, are produced in PW/tools:

•PW/tools/dist.x reads input data for PWscf, calculates distances and angles between

atoms in a cell, taking into account periodicity

•PW/tools/ev.x ﬁts energy-vs-volume data to an equation of state

•PW/tools/kpoints.x produces lists of k-points

•PW/tools/pwi2xsf.sh,pwo2xsf.sh process respectively input and output ﬁles (not data

ﬁles!) for pw.x and neb.x (the latter, courtesy of Pietro Bonf`a) and produce an XSF-

formatted ﬁle suitable for plotting with XCrySDen: http://www.xcrysden.org/, a pow-

erful crystalline and molecular structure visualization program. BEWARE: the pwi2xsf.sh

shell script requires the pwi2xsf.x executables to be located somewhere in your PATH.

•PW/tools/bs.awk,PW/tools/mv.awk are scripts that process the output of pw.x (not

data ﬁles!). Usage:

awk -f bs.awk < my-pw-file > myfile.bs

awk -f mv.awk < my-pw-file > myfile.mv

The ﬁles so produced are suitable for use with xbs, a very simple X-windows utility to

display molecules, available at:

http://www.ccl.net/cca/software/X-WINDOW/xbsa/README.shtml

•PW/tools/cif2qe.sh: script converting from CIF (Crystallographic Information File) to

a format suitable for Quantum ESPRESSO. Courtesy of Carlo Nervi (Univ. Torino,

Italy).

Documentation for the auxiliary codes can be found in the codes themselves, e.g. in the header

of ﬁles.

3 Using PWscf

Input ﬁles for pw.x may be either written by hand or produced via the PWgui graphical interface

by Anton Kokalj, included in the Quantum ESPRESSO distribution. See PWgui-x.y.z/INSTALL

(where x.y.z is the version number) for more info on PWgui, or GUI/README if you are using

SVN sources.

You may take the tests and examples distributed with Quantum ESPRESSO as templates

for writing your own input ﬁles. In the following, whenever we mention ”Example N”, we refer

to those. Input ﬁles are those in the results/ subdirectories, with names ending with .in

(they will appear after you have run the examples).

3.1 Input data

Input data is organized as several namelists, followed by other ﬁelds (“cards”) introduced by

keywords. The namelists are

&CONTROL: general variables controlling the run

&SYSTEM: structural information on the system under investigation

&ELECTRONS: electronic variables: self-consistency, smearing

&IONS (optional): ionic variables: relaxation, dynamics

&CELL (optional): variable-cell optimization or dynamics

Optional namelist may be omitted if the calculation to be performed does not require them.

This depends on the value of variable calculation in namelist &CONTROL. Most variables

in namelists have default values. Only the following variables in &SYSTEM must always be

speciﬁed:

ibrav (integer) Bravais-lattice index

celldm (real, dimension 6) crystallographic constants

nat (integer) number of atoms in the unit cell

ntyp (integer) number of types of atoms in the unit cell

ecutwfc (real) kinetic energy cutoﬀ (Ry) for wavefunctions.

For metallic systems, you have to specify how metallicity is treated in variable occupations.

If you choose occupations=’smearing’, you have to specify the smearing type smearing and

the smearing width degauss. Spin-polarized systems are as a rule treated as metallic system,

unless the total magnetization, tot magnetization is set to a ﬁxed value, or if occupation

numbers are ﬁxed (occupations=’from input’ and card OCCUPATIONS).

Explanations for the meaning of variables ibrav and celldm, as well as on alternative ways

to input structural data, are in ﬁles PW/Doc/INPUT PW.txt and PW/Doc/INPUT PW.html. These

ﬁles are the reference for input data and describe a large number of other variables as well.

Almost all variables have default values, which may or may not ﬁt your needs.

Comment lines in namelists can be introduced by a ”!”, exactly as in fortran code.

After the namelists, you have several ﬁelds (“cards”) introduced by keywords with self-

explanatory names:

ATOMIC SPECIES

ATOMIC POSITIONS

K POINTS

CELL PARAMETERS (optional)

OCCUPATIONS (optional)

The keywords may be followed on the same line by an option. Unknown ﬁelds are ignored. See

the ﬁles mentioned above for details on the available “cards”.

Comments lines in “cards” can be introduced by either a “!” or a “#” character in the ﬁrst

position of a line.

Note about k points: The k-point grid can be either automatically generated or manually

provided as a list of k-points and a weight in the Irreducible Brillouin Zone only of the Bravais

lattice of the crystal. The code will generate (unless instructed not to do so: see variable nosym)

all required k-points and weights if the symmetry of the system is lower than the symmetry of

the Bravais lattice. The automatic generation of k-points follows the convention of Monkhorst

and Pack.

3.2 Data ﬁles

The output data ﬁles are written in the directory outdir/prefix.save, as speciﬁed by vari-

ables outdir and prefix (a string that is prepended to all ﬁle names, whose default value is:

prefix=’pwscf’). outdir can be speciﬁed as well in environment variable ESPRESSO TMPDIR.

The iotk toolkit is used to write the ﬁle in a XML format, whose deﬁnition can be found in

the Developer Manual. In order to use the data directory on a diﬀerent machine, you should

convert the binary ﬁles to formatted, transfer them, convert them back to unformatted as in

the following example:

$bindir/iotk convert -t outdir/prefix.save/charge-density.dat myfile.txt

[ transfer file to the other machine ]

$bindir/iotk convert -b myfile.txt outdir/prefix.save/charge-density.dat

If you need wavefunctions as well, you must to set the pw.x option wf collect to .true.. In

such case, wavefunction ﬁles are found in directories outdir/prefix.save/K*, one per k-point.

You should do the conversion for all of them.

IMPORTANT NOTICE: starting with v.6, a new I/O system will replace the current one.

The execution stops if you create a ﬁle prefix.EXIT either in the working directory (i.e.

where the program is executed), or in the outdir directory. Note that with some versions of

MPI, the working directory is the directory where the executable is! The advantage of this

procedure is that all ﬁles are properly closed, whereas just killing the process may leave data

and output ﬁles in an unusable state.

3.3 Electronic structure calculations

Single-point (ﬁxed-ion) SCF calculation Set calculation=’scf’ (this is actually the

default). Namelists &IONS and &CELL will be ignored. For LSDA spin-polarized calculations

(that is: with a ﬁxed quantization axis for magnetization), set nspin=2. Note that the number

of k-points will be internally doubled (one set of k-points for spin-up, one set for spin-down).

See Example 01.

Band structure calculation First perform a SCF calculation as above; then do a non-SCF

calculation with the desired k-point grid and number nbnd of bands. Use calculation=’bands’

if you are interested in calculating only the Kohn-Sham states for the given set of k-points (e.g.

along symmetry lines: see for instance http://www.cryst.ehu.es/cryst/get kvec.html).

Specify instead calculation=’nscf’ if you are interested in further processing of the results of

non-SCF calculations (for instance, in DOS calculations). In the latter case, you should specify

a uniform grid of points. For DOS calculations you should choose occupations=’tetrahedra’,

together with an automatically generated uniform k-point grid (card K POINTS with option

“automatic”). Specify nosym=.true. to avoid generation of additional k-points in low symme-

try cases. Variables prefix and outdir, which determine the names of input or output ﬁles,

should be the same in the two runs. See Examples 01, 06, 07,

NOTA BENE: Since v.4.1, both atomic positions and the scf potential are read from the

data ﬁle so that consistency is guaranteed.

Noncollinear magnetization, spin-orbit interactions The following input variables are

relevant for noncollinear and spin-orbit calculations:

noncolin

lspinorb

starting magnetization (one for each type of atoms)

To make a spin-orbit calculation noncolin must be true. If starting magnetization is set

to zero (or not given) the code makes a spin-orbit calculation without spin magnetization (it

assumes that time reversal symmetry holds and it does not calculate the magnetization). The

states are still two-component spinors but the total magnetization is zero.

If starting magnetization is diﬀerent from zero, it makes a noncollinear spin polarized

calculation with spin-orbit interaction. The ﬁnal spin magnetization might be zero or diﬀerent

from zero depending on the system. Note that the code will look only for symmetries that leave

the starting magnetization unchanged.

Furthermore to make a spin-orbit calculation you must use fully relativistic pseudopoten-

tials at least for the atoms in which you think that spin-orbit interaction is large. If all the

pseudopotentials are scalar relativistic the calculation becomes equivalent to a noncollinear cal-

culation without spin orbit. (Andrea Dal Corso, 2007-07-27) See Example 06 for noncollinear

magnetism, Example 07 (and references quoted therein) for spin-orbit interactions.

DFT+U DFT+U (formerly known as LDA+U) calculation can be performed within a sim-

pliﬁed rotationally invariant form of the UHubbard correction. Note that for all atoms having

aUvalue there should be an item in function Modules/set hubbard l.f90 and one in sub-

routine PW/src/tabd.f90, deﬁning respectively the angular momentum and the occupancy of

the orbitals with the Hubbard correction. If your Hubbard-corrected atoms are not there, you

need to edit these ﬁles and to recompile.

See Example 08 and its README.

Dispersion Interactions (DFT-D) For DFT-D (DFT + semiempirical dispersion interac-

tions), see the description of input variables london*, sample ﬁles PW/tests/vdw.*, and the

comments in source ﬁle Modules/mm dispersion.f90.

Hartree-Fock and Hybrid functionals Since v.5.0, calculations in the Hartree-Fock ap-

proximation, or using hybrid XC functionals that include some Hartree-Fock exchange, no

longer require a special preprocessing before compilation. See EXX example/ and its README

ﬁle.

Dispersion interaction with non-local functional (vdW-DF) See example vdwDF example

and references quoted in ﬁle README therein.

Polarization via Berry Phase See Example 04, its ﬁle README, the documentation in

the header of PW/src/bp c phase.f90.

Finite electric ﬁelds There are two diﬀerent implementations of macroscopic electric ﬁelds

in pw.x: via an external sawtooth potential (input variable tefield=.true.) and via the

modern theory of polarizability (lelfield=.true.). The former is useful for surfaces, especially

in conjunction with dipolar corrections (dipfield=.true.): see examples/dipole example for

an example of application. Electric ﬁelds via modern theory of polarization are documented

in example 10. The exact meaning of the related variables, for both cases, is explained in the

general input documentation.

Orbital magnetization Modern theory of orbital magnetization [Phys. Rev. Lett. 95,

137205 (2005)] for insulators. The calculation is performed by setting input variable lorbm=.true.

in nscf run. If ﬁnite electric ﬁeld is present (lelfield=.true.) only Kubo terms are computed

[see New J. Phys. 12, 053032 (2010) for details].

3.4 Optimization and dynamics

Structural optimization For ﬁxed-cell optimization, specify calculation=’relax’ and

add namelist &IONS. All options for a single SCF calculation apply, plus a few others. You may

follow a structural optimization with a non-SCF band-structure calculation (since v.4.1, you

do not need any longer to update the atomic positions in the input ﬁle for non scf calculation).

See Example 02.

Molecular Dynamics Specify calculation=’md’, the time step dt, and possibly the num-

ber of MD stops nstep. Use variable ion dynamics in namelist &IONS for a ﬁne-grained

control of the kind of dynamics. Other options for setting the initial temperature and for

thermalization using velocity rescaling are available. Remember: this is MD on the electronic

ground state, not Car-Parrinello MD. See Example 03.

Free-energy surface calculations Once PWscf is patched with the PLUMED plug-in, it is

possible to use most PLUMED functionalities by running PWscf as: ./pw.x -plumed plus the

other usual PWscf arguments. The input ﬁle for PLUMED must be found in the speciﬁed outdir

with ﬁxed name plumed.dat.

Variable-cell optimization Since v.4.2 the newer BFGS algorithm covers the case of variable-

cell optimization as well. Note however that variable-cell calculations (both optimization and

dynamics) are performed with plane waves and G-vectors calculated for the starting cell. This

means that if you re-run a self-consistent calculation for the ﬁnal cell and atomic positions

using the same cutoﬀ ecutwfc (and/or ecutrho if applicable), you may not ﬁnd exactly the

same results, unless your ﬁnal and initial cells are very similar, or unless your cutoﬀ(s) are very

high. In order to provide a further check, a last step is performed in which a scf calculation is

performed for the converged structure, with plane waves and G-vectors calculated for the ﬁnal

cell. Small diﬀerences between the two last steps are thus to be expected and give an estimate

of the reliability of the variable-cell optimization. If you get a large diﬀerence, you are likely

quite far from convergence in the plane-wave basis set and you need to increase the cutoﬀ(s).

Variable-cell molecular dynamics ”A common mistake many new users make is to set the

time step dt improperly to the same order of magnitude as for CP algorithm, or not setting dt

at all. This will produce a “not evolving dynamics”. Good values for the original RMW (RM

Wentzcovitch) dynamics are dt = 50 ÷70. The choice of the cell mass is a delicate matter.

An oﬀ-optimal mass will make convergence slower. Too small masses, as well as too long time

steps, can make the algorithm unstable. A good cell mass will make the oscillation times for

internal degrees of freedom comparable to cell degrees of freedom in non-damped Variable-Cell

MD. Test calculations are advisable before extensive calculation. I have tested the damping

algorithm that I have developed and it has worked well so far. It allows for a much longer

time step (dt=100 ÷150) than the RMW one and is much more stable with very small cell

masses, which is useful when the cell shape, not the internal degrees of freedom, is far out of

equilibrium. It also converges in a smaller number of steps than RMW.” (Info from Cesar Da

Silva: the new damping algorithm is the default since v. 3.1).

3.5 Direct interface with CASINO

PWscf now supports the Cambridge quantum Monte Carlo program CASINO directly. For more

information on the CASINO code see http://www.tcm.phy.cam.ac.uk/~mdt26/casino.html.

CASINO may take the output of PWSCF and ’improve it’ giving considerably more accurate total

energies and other quantities than DFT is capable of.

PWscf users wishing to learn how to use CASINO may like to attend one of the annual

CASINO summer schools in Mike Towler’s ”Apuan Alps Centre for Physics” in Tuscany, Italy.

More information can be found at http://www.vallico.net/tti/tti.html

Practicalities The interface between PWscf and CASINO is provided through a ﬁle with a

standard format containing geometry, basis set, and orbital coeﬃcients, which PWscf will pro-

duce on demand. For SCF calculations, the name of this ﬁle may be pwfn.data,bwfn.data or

bwfn.data.b1 depending on user requests (see below). If the ﬁles are produced from an MD

run, the ﬁles have a suﬃx .0001,.0002,.0003 etc. corresponding to the sequence of timesteps.

CASINO support is implemented by three routines in the PW directory of the espresso distri-

bution:

•pw2casino.f90 : the main routine

•pw2casino write.f90 : writes the CASINO xwfn.data ﬁle in various formats

•pw2blip.f90 : does the plane-wave to blip conversion, if requested

Relevant behavior of PWscf may be modiﬁed through an optional auxiliary input ﬁle, named

pw2casino.dat (see below).

Note that in versions prior to 4.3, this functionality was provided through separate post-

processing utilities available in the PP directory: these are no longer supported. For QMC-MD

runs, PWSCF etc previously needed to be ’patched’ using the patch script PP/pw2casino-

MDloop.sh - this is no longer necessary.

How to generate xwfn.data ﬁles with PWscf Use the ’-pw2casino’ option when invoking

pw.x, e.g.:

pw.x -pw2casino < input_file > output_file

The xfwn.data ﬁle will then be generated automatically.

PWscf is capable of doing the plane wave to blip conversion directly (the ’blip’ utility

provided in the CASINO distribution is not required) and so by default, PWscf produces the

’binary blip wave function’ ﬁle bwfn.data.b1

Various options may be modiﬁed by providing a ﬁle pw2casino.dat in outdir with the

following format:

&inputpp

blip_convert=.true.

blip_binary=.true.

blip_single_prec=.false.

blip_multiplicity=1.d0

n_points_for_test=0

Some or all of the 5 keywords may be provided, in any order. The default values are as given

above (and these are used if the pw2casino.dat ﬁle is not present.

The meanings of the keywords are as follows:

blip convert : reexpand the converged plane-wave orbitals in localized blip functions prior to

writing the CASINO wave function ﬁle. This is almost always done, since wave functions

expanded in blips are considerably more eﬃcient in quantum Monte Carlo calculations. If

blip convert=.false. a pwfn.data ﬁle is produced (orbitals expanded in plane waves);

if blip convert=.true., either a bwfn.data file or a bwfn.data.b1 ﬁle is produced,

depending on the value of blip binary (see below).

blip binary : if true, and if blip convert is also true, write the blip wave function as an un-

formatted binary bwfn.data.b1 ﬁle. This is much smaller than the formatted bwfn.data

ﬁle, but is not generally portable across all machines.

blip single prec : if .false. the orbital coeﬃcients in bwfn.data(.b1) are written out in

double precision; if the user runs into hardware limits blip single prec can be set to

.true. in which case the coeﬃcients are written in single precision, reducing the memory

and disk requirements at the cost of a small amount of accuracy..

blip multiplicity : the quality of the blip expansion (i.e., the ﬁneness of the blip grid) can be

improved by increasing the grid multiplicity parameter given by this keyword. Increasing

the grid multiplicity results in a greater number of blip coeﬃcients and therefore larger

memory requirements and ﬁle size, but the CPU time should be unchanged. For very

accurate work, one may want to experiment with grid multiplicity larger that 1.0. Note,

however, that it might be more eﬃcient to keep the grid multiplicity to 1.0 and increase

the plane wave cutoﬀ instead.

n points for test : if this is set to a positive integer greater than zero, PWscf will sample the

wave function, the Laplacian and the gradient at a large number of random points in the

simulation cell and compute the overlap of the blip orbitals with the original plane-wave

orbitals:

α=< BW |P W >

q< BW |BW >< P W |P W >

The closer αis to 1, the better the blip representation. By increasing blip multiplicity,

or by increasing the plane-wave cutoﬀ, one ought to be able to make αas close to 1 as

desired. The number of random points used is given by n points for test.

Finally, note that DFT trial wave functions produced by PWSCF must be generated using

the same pseudopotential as in the subsequent QMC calculation. This requires the use of tools

to switch between the diﬀerent ﬁle formats used by the two codes.

CASINO uses the ‘CASINO tabulated format’, PWSCF oﬃcially supports the UPFv2 format

(though it will read other ‘deprecated’ formats). This can be done through the ‘casino2upf’

and ‘upf2casino’ tools included in the upftools directory (see the upftools/README ﬁle for

instructions). An alternative converter ‘casinogon’ is included in the CASINO distribution which

produces the deprecated GON format but which can be useful when using non-standard grids.

3.6 Socket interface with i-PI

The i-PI universal force engine performs advanced Molecular Dynamics (MD) (such as Path

Integral Molecular Dynamics, Thermodynamic Integration, Suzuki-Chin path integral, Multiple

Time Step molecular dynamics) and other force related computations (see ipi-code.org for

more information about i-PI).

PWscf users wishing to learn how to use i-PI should refer to the i-PI website.

Practicalities The communication between PWscf and i-PI relies on a socket interface. This

allows running i-PI and PWscf on diﬀerent computers provided that the two computers have

an Internet connection. Basically, i-PI works as a server waiting for a connection of a suit-

able software (for example PWscf). When this happens, i-PI injects atomic positions and cell

parameters into the software, that will return forces and stress tensor to i-PI.

The ﬁle containing the interface is run_driver.f90. The ﬁles socket.c and fsocket.f90

provide the necessary infrastructure to the socket interface.

How to use the i-PI inteface Since the communication goes through the Internet, the

PWscf instance needs to know the address of the i-PI server that can be speciﬁed with the

command line option --ipi (or -ipi) followed by the address of the computer running i-PI

and the port number where i-PI is listening, e.g.

pw.x --ipi localhost:3142 -in pw.input > pw.out

If i-PI and PWscf are running on the same machine, a UNIX socket is preferable since allows

faster communications, e.g.

pw.x --ipi socketname:UNIX -in pw.input > pw.out

In the last case, UNIX is a keyword that tells to PWscf to look for an UNIX socket connection

instead of an INET one. More extensive examples and tutorials can be found at ipi-code.org.

The PWscf input ﬁle must contain all the information to perform a single point calculation

(calculation = "scf") which are also used to initialize the PWscf run. Thus, it is important

that the PWscf input contains atomic positions and cell parameters which are as close as possible

to those speciﬁed in the i-PI input.

4 Performances

4.1 Execution time

The following is a rough estimate of the complexity of a plain scf calculation with pw.x, for

NCPP. USPP and PAW give raise additional terms to be calculated, that may add from a

few percent up to 30-40% to execution time. For phonon calculations, each of the 3Nat modes

requires a time of the same order of magnitude of self-consistent calculation in the same system

(possibly times a small multiple). For cp.x, each time step takes something in the order of

Th+Torth +Tsub deﬁned below.

The time required for the self-consistent solution at ﬁxed ionic positions, Tscf , is:

Tscf =NiterTiter +Tinit

where Niter = number of self-consistency iterations (niter), Titer = time for a single iteration,

Tinit = initialization time (usually much smaller than the ﬁrst term).

The time required for a single self-consistency iteration Titer is:

Titer =NkTdiag +Trho +Tscf

where Nk= number of k-points, Tdiag = time per Hamiltonian iterative diagonalization, Trho

= time for charge density calculation, Tscf = time for Hartree and XC potential calculation.

The time for a Hamiltonian iterative diagonalization Tdiag is:

Tdiag =NhTh+Torth +Tsub

where Nh= number of Hψ products needed by iterative diagonalization, Th= time per Hψ

product, Torth = CPU time for orthonormalization, Tsub = CPU time for subspace diagonaliza-

tion.

The time Threquired for a Hψ product is

Th=a1MN +a2MN1N2N3log(N1N2N3) + a3M P N.

The ﬁrst term comes from the kinetic term and is usually much smaller than the others. The

second and third terms come respectively from local and nonlocal potential. a1, a2, a3are

prefactors (i.e. small numbers O(1)), M= number of valence bands (nbnd), N= number of

PW (basis set dimension: npw), N1, N2, N3= dimensions of the FFT grid for wavefunctions

(nr1s,nr2s,nr3s;N1N2N3∼8N), P = number of pseudopotential projectors, summed on

all atoms, on all values of the angular momentum l, and m= 1, ..., 2l+ 1.

The time Torth required by orthonormalization is

Torth =b1NM2

and the time Tsub required by subspace diagonalization is

Tsub =b2M3

where b1and b2are prefactors, Mx= number of trial wavefunctions (this will vary between M

and 2 ÷4M, depending on the algorithm).

The time Trho for the calculation of charge density from wavefunctions is

Trho =c1MNr1Nr2Nr3log(Nr1Nr2Nr3) + c2MNr1Nr2Nr3+Tus

where c1, c2, c3are prefactors, Nr1, Nr2, Nr3= dimensions of the FFT grid for charge density

(nr1,nr2,nr3;Nr1Nr2Nr3∼8Ng, where Ng= number of G-vectors for the charge density,

ngm), and Tus = time required by PAW/USPPs contribution (if any). Note that for NCPPs

the FFT grids for charge and wavefunctions are the same.

The time Tscf for calculation of potential from charge density is

Tscf =d2Nr1Nr2Nr3+d3Nr1Nr2Nr3log(Nr1Nr2Nr3)

where d1, d2are prefactors.

For hybrid DFTs, the dominant term is by far the calculation of the nonlocal (Vxψ) product,

taking as much as

Texx =eNkNqM2N1N2N3log(N1N2N3)

where Nqis the number of points in the k+qgrid, determined by options nqx1,nqx2,nqx3,e

is a prefactor.

The above estimates are for serial execution. In parallel execution, each contribution may

scale in a diﬀerent manner with the number of processors (see below).

4.2 Memory requirements

A typical self-consistency or molecular-dynamics run requires a maximum memory in the order

of Odouble precision complex numbers, where

O=mMN +P N +pN1N2N3+qNr1Nr2Nr3

with m, p, q = small factors; all other variables have the same meaning as above. Note that if

the Γ−point only (k= 0) is used to sample the Brillouin Zone, the value of N will be cut into

half.

For hybrid DFTs, additional storage of Oxdouble precision complex numbers is needed (for

Fourier-transformed Kohn-Sham states), with Ox=xNqMN1N2N3and x= 0.5 for Γ−only

calculations, x= 1 otherwise.

The memory required by the phonon code follows the same patterns, with somewhat larger

factors m, p, q.

4.3 File space requirements

A typical pw.x run will require an amount of temporary disk space in the order of O double

precision complex numbers:

O=NkMN +qNr1Nr2Nr3

where q= 2×mixing ndim (number of iterations used in self-consistency, default value = 8) if

disk io is set to ’high’; q = 0 otherwise.

4.4 Parallelization issues

pw.x can run in principle on any number of processors. The eﬀectiveness of parallelization is

ultimately judged by the ”scaling”, i.e. how the time needed to perform a job scales with the

number of processors, and depends upon:

•the size and type of the system under study;

•the judicious choice of the various levels of parallelization (detailed in Sec.4.4);

•the availability of fast interprocess communications (or lack of it).

Ideally one would like to have linear scaling, i.e. T∼T0/Npfor Npprocessors, where T0is

the estimated time for serial execution. In addition, one would like to have linear scaling of

the RAM per processor: ON∼O0/Np, so that large-memory systems ﬁt into the RAM of each

processor.

Parallelization on k-points:

•guarantees (almost) linear scaling if the number of k-points is a multiple of the number

of pools;

•requires little communications (suitable for ethernet communications);

•reduces the required memory per processor by distributing wavefunctions (but not other

quantities like the charge density), unless you set disk io=’high’.

Parallelization on PWs:

•yields good to very good scaling, especially if the number of processors in a pool is a

divisor of N3and Nr3(the dimensions along the z-axis of the FFT grids, nr3 and nr3s,

which coincide for NCPPs);

•requires heavy communications (suitable for Gigabit ethernet up to 4, 8 CPUs at most,

specialized communication hardware needed for 8 or more processors );

•yields almost linear reduction of memory per processor with the number of processors in

the pool.

A note on scaling: optimal serial performances are achieved when the data are as much as

possible kept into the cache. As a side eﬀect, PW parallelization may yield superlinear (better

than linear) scaling, thanks to the increase in serial speed coming from the reduction of data

size (making it easier for the machine to keep data in the cache).

VERY IMPORTANT: For each system there is an optimal range of number of processors on

which to run the job. A too large number of processors will yield performance degradation. If

the size of pools is especially delicate: Npshould not exceed N3and Nr3, and should ideally be

no larger than 1/2÷1/4N3and/or Nr3. In order to increase scalability, it is often convenient

to further subdivide a pool of processors into ”task groups”. When the number of processors

exceeds the number of FFT planes, data can be redistributed to ”task groups” so that each

group can process several wavefunctions at the same time.

The optimal number of processors for ”linear-algebra” parallelization, taking care of mul-

tiplication and diagonalization of M×Mmatrices, should be determined by observing the

performances of cdiagh/rdiagh (pw.x) or ortho (cp.x) for diﬀerent numbers of processors in

the linear-algebra group (must be a square integer).

Actual parallel performances will also depend on the available software (MPI libraries) and

on the available communication hardware. For PC clusters, OpenMPI (http://www.openmpi.org/)

seems to yield better performances than other implementations (info by Kostantin Kudin). Note

however that you need a decent communication hardware (at least Gigabit ethernet) in order

to have acceptable performances with PW parallelization. Do not expect good scaling with

cheap hardware: PW calculations are by no means an ”embarrassing parallel” problem.

Also note that multiprocessor motherboards for Intel Pentium CPUs typically have just one

memory bus for all processors. This dramatically slows down any code doing massive access to

memory (as most codes in the Quantum ESPRESSO distribution do) that runs on processors

of the same motherboard.

4.5 Understanding the time report

The time report printed at the end of a pw.x run contains a lot of useful information that can

be used to understand bottlenecks and improve performances.

4.5.1 Serial execution

The following applies to calculations taking a sizable amount of time (at least minutes): for short

calculations (seconds), the time spent in the various initializations dominates. Any discrepancy

with the following picture signals some anomaly.

•For a typical job with norm-conserving PPs, the total (wall) time is mostly spent in

routine ”electrons”, calculating the self-consistent solution.

•Most of the time spent in ”electrons” is used by routine ”c bands”, calculating Kohn-

Sham states. ”sum band” (calculating the charge density), ”v of rho” (calculating the

potential), ”mix rho” (charge density mixing) should take a small fraction of the time.

•Most of the time spent in ”c bands” is used by routines ”cegterg” (k-points) or ”regterg”

(Gamma-point only), performing iterative diagonalization of the Kohn-Sham Hamiltonian

in the PW basis set.

•Most of the time spent in ”*egterg” is used by routine ”h psi”, calculating Hψ products.

”cdiaghg” (k-points) or ”rdiaghg” (Gamma-only), performing subspace diagonalization,

should take only a small fraction.

•Among the ”general routines”, most of the time is spent in FFT on Kohn-Sham states:

”ﬀtw”, and to a smaller extent in other FFTs, ”ﬀt” and ”ﬀts”, and in ”calbec”, calculating

hψ|βiproducts.

•Forces and stresses typically take a fraction of the order of 10 to 20% of the total time.

For PAW and Ultrasoft PP, you will see a larger contribution by ”sum band” and a nonnegligible

”newd” contribution to the time spent in ”electrons”, but the overall picture is unchanged. You

may drastically reduce the overhead of Ultrasoft PPs by using input option ”tqr=.true.”.

4.5.2 Parallel execution

The various parallelization levels should be used wisely in order to achieve good results. Let

us summarize the eﬀects of them on CPU:

•Parallelization on FFT speeds up (with varying eﬃciency) almost all routines, with the

notable exception of ”cdiaghg” and ”rdiaghg”.

•Parallelization on k-points speeds up (almost linearly) ”c bands” and called routines;

speeds up partially ”sum band”; does not speed up at all ”v of rho”, ”newd”, ”mix rho”.

•Linear-algebra parallelization speeds up (not always) ”cdiaghg” and ”rdiaghg”

•”task-group” parallelization speeds up ”ﬀtw”

•OpenMP parallelization speeds up ”ﬀtw”, plus selected parts of the calculation, plus

(depending on the availability of OpenMP-aware libraries) some linear algebra operations

and on RAM:

•Parallelization on FFT distributes most arrays across processors (i.e. all G-space and R-

spaces arrays) but not all of them (in particular, not subspace Hamiltonian and overlap

matrices)

•Linear-algebra parallelization also distributes subspace Hamiltonian and overlap matrices.

•All other parallelization levels do not distribute any memory

In an ideally parallelized run, you should observe the following:

•CPU and wall time do not diﬀer by much

•Time usage is still dominated by the same routines as for the serial run

•Routine ”ﬀt scatter” (called by parallel FFT) takes a sizable part of the time spent in

FFTs but does not dominate it.

Quick estimate of parallelization parameters You need to know

•the number of k-points, Nk

•the third dimension of the (smooth) FFT grid, N3

•the number of Kohn-Sham states, M

These data allow to set bounds on parallelization:

•k-point parallelization is limited to Nkprocessor pools: -nk Nk

•FFT parallelization shouldn’t exceed N3processors, i.e. if you run with -nk Nk, use

N=Nk×N3MPI processes at most (mpirun -np N ...)

•Unless Mis a few hundreds or more, don’t bother using linear-algebra parallelization

You will need to experiment a bit to ﬁnd the best compromise. In order to have good load

balancing among MPI processes, the number of k-point pools should be an integer divisor of

Nk; the number of processors for FFT parallelization should be an integer divisor of N3.

Typical symptoms of bad/inadequate parallelization

•a large fraction of time is spent in ”v of rho”, ”newd”, ”mix rho”, or

the time doesn’t scale well or doesn’t scale at all by increasing the number of processors

for k-point parallelization. Solution:

–use (also) FFT parallelization if possible

•a disproportionate time is spent in ”cdiaghg”/”rdiaghg”. Solutions:

–use (also) k-point parallelization if possible

–use linear-algebra parallelization, with scalapack if possible.

•a disproportionate time is spent in ”ﬀt scatter”, or in ”ﬀt scatter” the diﬀerence between

CPU and wall time is large. Solutions:

–if you do not have fast (better than Gigabit ethernet) communication hardware, do

not try FFT parallelization on more than 4 or 8 procs.

–use (also) k-point parallelization if possible

•the time doesn’t scale well or doesn’t scale at all by increasing the number of processors

for FFT parallelization. Solutions:

–use ”task groups”: try command-line option -ntg 4 or -ntg 8. This may improve

your scaling.

4.6 Restarting

Since QE 5.1 restarting from an arbitrary point of the code is no more supported.

The code must terminate properly in order for restart to be possible. A clean stop can be

triggered by one the following three conditions:

1. The amount of time speciﬁed by the input variable max seconds is reached

2. The user creates a ﬁle named ”$preﬁx.EXIT” either in the working directory or in output

directory ”$outdir” (variables $outdir and $preﬁx as speciﬁed in the control namelist)

3. (experimental) The code is compiled with signal-trapping support and one of the trapped

signals is received (see the next section for details).

After the condition is met, the code will try to stop cleanly as soon as possible, which can

take a while for large calculation. Writing the ﬁles to disk can also be a long process. In order

to be safe you need to reserve suﬃcient time for the stop process to complete.

If the previous execution of the code has stopped properly, restarting is possible setting

restart mode=“restart” in the control namelist.

4.6.1 Signal trapping (experimental!)

In order to compile signal-trapping add ”-D TERMINATE GRACEFULLY” to MANUAL DFLAGS

in the make.doc ﬁle. Currently the code intercepts SIGINT, SIGTERM, SIGUSR1, SIGUSR2,

SIGXCPU; signals can be added or removed editing the ﬁle clib/custom signals.c.

Common queue systems will send a signal some time before killing a job. The exact be-

haviour depends on the queue systems and could be conﬁgured. Some examples:

With PBS:

•send the default signal (SIGTERM) 120 seconds before the end:

#PBS -l signal=@120

•send signal SIGUSR1 10 minutes before the end:

#PBS -l signal=SIGUSR1@600

•you cand also send a signal manually with qsig

•or send a signal and then stop:

qdel -W 120 jobid

will send SIGTERM, wait 2 minutes than force stop.

With LoadLeveler (untested): the SIGXCPU signal will be sent when wall softlimit is

reached, it will then stop the job when hardlimit is reached. You can specify both limits as:

# @ wall clock limit = hardlimit,softlimit

e.g. you can give pw.x thirty minutes to stop using:

# @ wall clock limit = 5:00,4:30

5 Troubleshooting

pw.x says ’error while loading shared libraries’ or ’cannot open shared object ﬁle’

and does not start Possible reasons:

•If you are running on the same machines on which the code was compiled, this is a library

conﬁguration problem. The solution is machine-dependent. On Linux, ﬁnd the path to

the missing libraries; then either add it to ﬁle /etc/ld.so.conf and run ldconfig (must

be done as root), or add it to variable LD LIBRARY PATH and export it. Another

possibility is to load non-shared version of libraries (ending with .a) instead of shared

ones (ending with .so).

•If you are not running on the same machines on which the code was compiled: you need

either to have the same shared libraries installed on both machines, or to load statically all

libraries (using appropriate configure or loader options). The same applies to Beowulf-

style parallel machines: the needed shared libraries must be present on all PCs.

errors in examples with parallel execution If you get error messages in the exam-

ple scripts – i.e. not errors in the codes – on a parallel machine, such as e.g.: run exam-

ple: -n: command not found you may have forgotten to properly deﬁne PARA PREFIX and

PARA POSTFIX.

pw.x prints the ﬁrst few lines and then nothing happens (parallel execution) If

the code looks like it is not reading from input, maybe it isn’t: the MPI libraries need to be

properly conﬁgured to accept input redirection. Use pw.x -i and the input ﬁle name (see

Sec.4.4), or inquire with your local computer wizard (if any). Since v.4.2, this is for sure the

reason if the code stops at Waiting for input....

pw.x stops with error while reading data There is an error in the input data, typically

a misspelled namelist variable, or an empty input ﬁle. Unfortunately with most compilers the

code just reports Error while reading XXX namelist and no further useful information. Here

are some more subtle sources of trouble:

•Out-of-bound indices in dimensioned variables read in the namelists;

•Input data ﬁles containing ˆM (Control-M) characters at the end of lines, or non-ASCII

characters (e.g. non-ASCII quotation marks, that at a ﬁrst glance may look the same

as the ASCII character). Typically, this happens with ﬁles coming from Windows or

produced with ”smart” editors.

Both may cause the code to crash with rather mysterious error messages. If none of the above

applies and the code stops at the ﬁrst namelist (&CONTROL) and you are running in parallel,

see the previous item.

pw.x mumbles something like cannot recover or error reading recover ﬁle You are

trying to restart from a previous job that either produced corrupted ﬁles, or did not do what

you think it did. No luck: you have to restart from scratch.

pw.x stops with inconsistent DFT error As a rule, the ﬂavor of DFT used in the

calculation should be the same as the one used in the generation of pseudopotentials, which

should all be generated using the same ﬂavor of DFT. This is actually enforced: the type of

DFT is read from pseudopotential ﬁles and it is checked that the same DFT is read from all

PPs. If this does not hold, the code stops with the above error message. Use – at your own

risk – input variable input dft to force the usage of the DFT you like.

pw.x stops with error in cdiaghg or rdiaghg Possible reasons for such behavior are not

always clear, but they typically fall into one of the following cases:

•serious error in data, such as bad atomic positions or bad crystal structure/supercell;

•a bad pseudopotential, typically with a ghost, or a USPP giving non-positive charge

density, leading to a violation of positiveness of the S matrix appearing in the USPP

formalism;

•a failure of the algorithm performing subspace diagonalization. The LAPACK algorithms

used by cdiaghg (for generic k-points) or rdiaghg (for Γ−only case) are very robust and

extensively tested. Still, it may seldom happen that such algorithms fail. Try to use

conjugate-gradient diagonalization (diagonalization=’cg’), a slower but very robust

algorithm, and see what happens.

•buggy libraries. Machine-optimized mathematical libraries are very fast but sometimes

not so robust from a numerical point of view. Suspicious behavior: you get an error

that is not reproducible on other architectures or that disappears if the calculation is

repeated with even minimal changes in parameters. Known cases: HP-Compaq alphas

with cxml libraries, Mac OS-X with system BLAS/LAPACK. Try to use compiled BLAS

and LAPACK (or better, ATLAS) instead of machine-optimized libraries.

pw.x crashes with no error message at all This happens quite often in parallel execu-

tion, or under a batch queue, or if you are writing the output to a ﬁle. When the program

crashes, part of the output, including the error message, may be lost, or hidden into error ﬁles

where nobody looks into. It is the fault of the operating system, not of the code. Try to run

interactively and to write to the screen. If this doesn’t help, move to next point.

pw.x crashes with segmentation fault or similarly obscure messages Possible rea-

sons:

•too much RAM memory or stack requested (see next item).

•if you are using highly optimized mathematical libraries, verify that they are designed for

your hardware.

•If you are using aggressive optimization in compilation, verify that you are using the

appropriate options for your machine

•The executable was not properly compiled, or was compiled on a diﬀerent and incompat-

ible environment.

•buggy compiler or libraries: this is the default explanation if you have problems with the

provided tests and examples.

pw.x works for simple systems, but not for large systems or whenever more RAM

is needed Possible solutions:

•Increase the amount of RAM you are authorized to use (which may be much smaller than

the available RAM). Ask your system administrator if you don’t know what to do. In

some cases the stack size can be a source of problems: if so, increase it with command

limits or ulimit).

•Reduce nbnd to the strict minimum (for insulators, the default is already the minimum,

though).

•Reduce the work space for Davidson diagonalization to the minimum by setting diago david ndim=2;

also consider using conjugate gradient diagonalization (diagonalization=’cg’), slow but

very robust, which requires almost no work space.

•If the charge density takes a signiﬁcant amount of RAM, reduce mixing ndim from its

default value (8) to 4 or so.

•In parallel execution, use more processors, or use the same number of processors with less

pools. Remember that parallelization with respect to k-points (pools) does not distribute

memory: only parallelization with respect to R- (and G-) space does.

•If none of the above is suﬃcient or feasible, you have to either reduce the cutoﬀs and/or

the cell size, or to use a machine with more RAM.

pw.x crashes with error in davcio davcio is the routine that performs most of the I/O

operations (read from disk and write to disk) in pw.x;error in davcio means a failure of an

I/O operation.

•If the error is reproducible and happens at the beginning of a calculation: check if you

have read/write permission to the scratch directory speciﬁed in variable outdir. Also:

check if there is enough free space available on the disk you are writing to, and check your

disk quota (if any).

•If the error is irreproducible: your might have ﬂaky disks; if you are writing via the

network using NFS (which you shouldn’t do anyway), your network connection might be

not so stable, or your NFS implementation is unable to work under heavy load

•If it happens while restarting from a previous calculation: you might be restarting from

the wrong place, or from wrong data, or the ﬁles might be corrupted. Note that, since

QE 5.1, restarting from arbitrary places is no more supported: the code must terminate

cleanly.

•If you are running two or more instances of pw.x at the same time, check if you are using

the same ﬁle names in the same temporary directory. For instance, if you submit a series

of jobs to a batch queue, do not use the same outdir and the same prefix, unless you

are sure that one job doesn’t start before a preceding one has ﬁnished.

pw.x crashes in parallel execution with an obscure message related to MPI errors

Random crashes due to MPI errors have often been reported, typically in Linux PC clusters.

We cannot rule out the possibility that bugs in Quantum ESPRESSO cause such behavior,

but we are quite conﬁdent that the most likely explanation is a hardware problem (defective

RAM for instance) or a software bug (in MPI libraries, compiler, operating system).

Debugging a parallel code may be diﬃcult, but you should at least verify if your problem is

reproducible on diﬀerent architectures/software conﬁgurations/input data sets, and if there is

some particular condition that activates the bug. If this doesn’t seem to happen, the odds are

that the problem is not in Quantum ESPRESSO. You may still report your problem, but

consider that reports like it crashes with...(obscure MPI error) contain 0 bits of information

and are likely to get 0 bits of answers.

pw.x stops with error message the system is metallic, specify occupations You did

not specify state occupations, but you need to, since your system appears to have an odd number

of electrons. The variable controlling how metallicity is treated is occupations in namelist

&SYSTEM. The default, occupations=’fixed’, occupies the lowest (N electrons)/2 states

and works only for insulators with a gap. In all other cases, use ’smearing’ (’tetrahedra’

for DOS calculations). See input reference documentation for more details.

pw.x stops with internal error: cannot bracket Ef Possible reasons:

•serious error in data, such as bad number of electrons, insuﬃcient number of bands,

absurd value of broadening;

•the Fermi energy is found by bisection assuming that the integrated DOS N(E ) is an in-

creasing function of the energy. This is not guaranteed for Methfessel-Paxton smearing of

order 1 and can give problems when very few k-points are used. Use some other smearing

function: simple Gaussian broadening or, better, Marzari-Vanderbilt ’cold smearing’.

pw.x yields internal error: cannot bracket Ef message but does not stop This may

happen under special circumstances when you are calculating the band structure for selected

high-symmetry lines. The message signals that occupations and Fermi energy are not correct

(but eigenvalues and eigenvectors are). Remove occupations=’tetrahedra’ in the input data

to get rid of the message.

pw.x runs but nothing happens Possible reasons:

•in parallel execution, the code died on just one processor. Unpredictable behavior may

follow.

•in serial execution, the code encountered a ﬂoating-point error and goes on producing

NaNs (Not a Number) forever unless exception handling is on (and usually it isn’t). In

both cases, look for one of the reasons given above.

•maybe your calculation will take more time than you expect.

pw.x yields weird results If results are really weird (as opposed to misinterpreted):

•if this happens after a change in the code or in compilation or preprocessing options, try

make clean, recompile. The make command should take care of all dependencies, but do

not rely too heavily on it. If the problem persists, recompile with reduced optimization

level.

•maybe your input data are weird.

FFT grid is machine-dependent Yes, they are! The code automatically chooses the small-

est grid that is compatible with the speciﬁed cutoﬀ in the speciﬁed cell, and is an allowed value

for the FFT library used. Most FFT libraries are implemented, or perform well, only with

dimensions that factors into products of small numbers (2, 3, 5 typically, sometimes 7 and 11).

Diﬀerent FFT libraries follow diﬀerent rules and thus diﬀerent dimensions can result for the

same system on diﬀerent machines (or even on the same machine, with a diﬀerent FFT). See

function allowed in Modules/fft scalar.f90.

As a consequence, the energy may be slightly diﬀerent on diﬀerent machines. The only

piece that explicitly depends on the grid parameters is the XC part of the energy that is

computed numerically on the grid. The diﬀerences should be small, though, especially for LDA

calculations.

Manually setting the FFT grids to a desired value is possible, but slightly tricky, using

input variables nr1,nr2,nr3 and nr1s,nr2s,nr3s. The code will still increase them if not

acceptable. Automatic FFT grid dimensions are slightly overestimated, so one may try very

carefully to reduce them a little bit. The code will stop if too small values are required, it will

waste CPU time and memory for too large values.

Note that in parallel execution, it is very convenient to have FFT grid dimensions along z

that are a multiple of the number of processors.

pw.x does not ﬁnd all the symmetries you expected pw.x determines ﬁrst the symmetry

operations (rotations) of the Bravais lattice; then checks which of these are symmetry operations

of the system (including if needed fractional translations). This is done by rotating (and

translating if needed) the atoms in the unit cell and verifying if the rotated unit cell coincides

with the original one.

Assuming that your coordinates are correct (please carefully check!), you may not ﬁnd all

the symmetries you expect because:

•the number of signiﬁcant ﬁgures in the atomic positions is not large enough. In ﬁle

PW/eqvect.f90, the variable accep is used to decide whether a rotation is a symmetry

operation. Its current value (10−5) is quite strict: a rotated atom must coincide with

another atom to 5 signiﬁcant digits. You may change the value of accep and recompile.

•they are not acceptable symmetry operations of the Bravais lattice. This is the case

for C60, for instance: the Ihicosahedral group of C60 contains 5-fold rotations that are

incompatible with translation symmetry.

•the system is rotated with respect to symmetry axis. For instance: a C60 molecule in the

fcc lattice will have 24 symmetry operations (Thgroup) only if the double bond is aligned

along one of the crystal axis; if C60 is rotated in some arbitrary way, pw.x may not ﬁnd

any symmetry, apart from inversion.

•they contain a fractional translation that is incompatible with the FFT grid (see next

paragraph). Note that if you change cutoﬀ or unit cell volume, the automatically com-

puted FFT grid changes, and this may explain changes in symmetry (and in the number

of k-points as a consequence) for no apparent good reason (only if you have fractional

translations in the system, though).

•a fractional translation, without rotation, is a symmetry operation of the system. This

means that the cell is actually a supercell. In this case, all symmetry operations containing

fractional translations are disabled. The reason is that in this rather exotic case there is no

simple way to select those symmetry operations forming a true group, in the mathematical

sense of the term.

Warning: symmetry operation # N not allowed This is not an error. If a symmetry

operation contains a fractional translation that is incompatible with the FFT grid, it is discarded

in order to prevent problems with symmetrization. Typical fractional translations are 1/2

or 1/3 of a lattice vector. If the FFT grid dimension along that direction is not divisible

respectively by 2 or by 3, the symmetry operation will not transform the FFT grid into itself.

Solution: you can either force your FFT grid to be commensurate with fractional translation

(set variables nr1,nr2,nr3 to suitable values), or set variable use all frac to .true., in

namelist &SYSTEM. Note however that the latter is incompatible with hybrid functionals and

with phonon calculations.

Self-consistency is slow or does not converge at all Bad input data will often result in

bad scf convergence. Please carefully check your structure ﬁrst, e.g. using XCrySDen.

Assuming that your input data is sensible :

1. Verify if your system is metallic or is close to a metallic state, especially if you have few

k-points. If the highest occupied and lowest unoccupied state(s) keep exchanging place

during self-consistency, forget about reaching convergence. A typical sign of such behavior

is that the self-consistency error goes down, down, down, than all of a sudden up again,

and so on. Usually one can solve the problem by adding a few empty bands and a small

broadening.

2. Reduce mixing beta to ∼0.3÷0.1 or smaller. Try the mixing mode value that is more

appropriate for your problem. For slab geometries used in surface problems or for elon-

gated cells, mixing mode=’local-TF’ should be the better choice, dampening ”charge

sloshing”. You may also try to increase mixing ndim to more than 8 (default value).

Beware: this will increase the amount of memory you need.

3. Speciﬁc to USPP: the presence of negative charge density regions due to either the

pseudization procedure of the augmentation part or to truncation at ﬁnite cutoﬀ may

give convergence problems. Raising the ecutrho cutoﬀ for charge density will usually

help.

I do not get the same results in diﬀerent machines! If the diﬀerence is small, do not

panic. It is quite normal for iterative methods to reach convergence through diﬀerent paths

as soon as anything changes. In particular, between serial and parallel execution there are

operations that are not performed in the same order. As the numerical accuracy of computer

numbers is ﬁnite, this can yield slightly diﬀerent results.

It is also normal that the total energy converges to a better accuracy than its terms, since

only the sum is variational, i.e. has a minimum in correspondence to ground-state charge

density. Thus if the convergence threshold is for instance 10−8, you get 8-digit accuracy on

the total energy, but one or two less on other terms (e.g. XC and Hartree energy). It this

is a problem for you, reduce the convergence threshold for instance to 10−10 or 10−12. The

diﬀerences should go away (but it will probably take a few more iterations to converge).

Execution time is time-dependent! Yes it is! On most machines and on most operating

systems, depending on machine load, on communication load (for parallel machines), on various

other factors (including maybe the phase of the moon), reported execution times may vary quite

a lot for the same job.

Warning : N eigenvectors not converged This is a warning message that can be safely

ignored if it is not present in the last steps of self-consistency. If it is still present in the last

steps of self-consistency, and if the number of unconverged eigenvector is a signiﬁcant part of

the total, it may signal serious trouble in self-consistency (see next point) or something badly

wrong in input data.

Warning : negative or imaginary charge..., or ...core charge ..., or npt with

rhoup<0... or rho dw<0... These are warning messages that can be safely ignored unless

the negative or imaginary charge is sizable, let us say of the order of 0.1. If it is, something

seriously wrong is going on. Otherwise, the origin of the negative charge is the following. When

one transforms a positive function in real space to Fourier space and truncates at some ﬁnite

cutoﬀ, the positive function is no longer guaranteed to be positive when transformed back to

real space. This happens only with core corrections and with USPPs. In some cases it may

be a source of trouble (see next point) but it is usually solved by increasing the cutoﬀ for the

charge density.

Structural optimization is slow or does not converge or ends with a mysterious

bfgs error Typical structural optimizations, based on the BFGS algorithm, converge to the

default thresholds ( etot conv thr and forc conv thr ) in 15-25 BFGS steps (depending on the

starting conﬁguration). This may not happen when your system is characterized by ”ﬂoppy”

low-energy modes, that make very diﬃcult (and of little use anyway) to reach a well converged

structure, no matter what. Other possible reasons for a problematic convergence are listed

below.

Close to convergence the self-consistency error in forces may become large with respect to

the value of forces. The resulting mismatch between forces and energies may confuse the line

minimization algorithm, which assumes consistency between the two. The code reduces the

starting self-consistency threshold conv thr when approaching the minimum energy conﬁgura-

tion, up to a factor deﬁned by upscale. Reducing conv thr (or increasing upscale) yields a

smoother structural optimization, but if conv thr becomes too small, electronic self-consistency

may not converge. You may also increase variables etot conv thr and forc conv thr that

determine the threshold for convergence (the default values are quite strict).

A limitation to the accuracy of forces comes from the absence of perfect translational in-

variance. If we had only the Hartree potential, our PW calculation would be translationally

invariant to machine precision. The presence of an XC potential introduces Fourier components

in the potential that are not in our basis set. This loss of precision (more serious for gradient-

corrected functionals) translates into a slight but detectable loss of translational invariance (the

energy changes if all atoms are displaced by the same quantity, not commensurate with the

FFT grid). This sets a limit to the accuracy of forces. The situation improves somewhat by

increasing the ecutrho cutoﬀ.

pw.x stops during variable-cell optimization in checkallsym with non orthogonal

operation error Variable-cell optimization may occasionally break the starting symmetry of

the cell. When this happens, the run is stopped because the number of k-points calculated for

the starting conﬁguration may no longer be suitable. Possible solutions:

•start with a nonsymmetric cell;

•use a symmetry-conserving algorithm: the Wentzcovitch algorithm (cell dynamics=’damp-w’)

should not break the symmetry.

5.1 Compilation problems with PLUMED

xlc compiler If you get an error message like:

Operation between types "char**" and "int" is not allowed.

change in ﬁle clib/metadyn.h

#define snew(ptr,nelem) (ptr)= (nelem==0 ? NULL : (typeof(ptr)) calloc(nelem, sizeof(*(ptr))))

#define srenew(ptr,nelem) (ptr)= (typeof(ptr)) realloc(ptr,(nelem)*sizeof(*(ptr)))

with

#define snew(ptr,nelem) (ptr)= (nelem==0 ? NULL : (void*) calloc(nelem, sizeof(*(ptr))))

#define srenew(ptr,nelem) (ptr)= (void*) realloc(ptr,(nelem)*sizeof(*(ptr)))

Calling C from fortran PLUMED assumes that fortran compilers add a single at the end

of C routines. You may get an error message as :

ERROR: Undefined symbol: .init_metadyn

ERROR: Undefined symbol: .meta_force_calculation

eliminate the from the deﬁnition of init metadyn and meta force calculation, i. e. change at

line 529

void meta_force_calculation_(real *cell, int *istep, real *xxx, real *yyy, real *zzz,

with

void meta_force_calculation(real *cell, int *istep, real *xxx, real *yyy, real *zzz,

, and at line 961

void init_metadyn_(int *atoms, real *ddt, real *mass,

User Guide

user_guide

Navigation menu

Versions of this User Manual:

Views

Navigation