INSTALL

====== How to compile the CP2K code ======

This document is maintained in the svn-repository as cp2k/INSTALL .
A nicely rendered version of it can be found at https://cp2k.org/howto:compile .

=====  1. Acquire the code: =====

see  https://www.cp2k.org/download

For users, the preferred method is to download a release.
For developers, the preferred method is to download it from the SVN.

===== 2. Install Prerequisites =====
Sub-points here discuss prerequisites needed to build CP2K.
Some of these can be conveniently installed by a script see: cp2k/tools/toolchain
Copies of the recommended versions of 3rd party software can be
downloaded from https://www.cp2k.org/static/downloads/ .

==== 2a. GNU make (required, build system) ====
GNU make should be on your system (gmake or make on linux) and used for
the build, go to https://www.gnu.org/software/make/make.html
download from https://ftp.gnu.org/pub/gnu/make/
also python (2.X) is required for building.

==== 2b. Python (required, build system) ====
python 2.x is needed to run the dependency generator.
On most system python is already installed.
For more information visit: https://www.python.org/


==== 2c. Fortran and C Compiler (required, build system) ====
A Fortran 2003 compiler and matching C compiler should be installed on your system.
We have good experience with gcc/gfortran (gcc >=4.6 works, later version recommended).
Be aware that some compilers have bugs that might cause them to fail (internal compiler errors,
segfaults) or, worse, yield a mis-compiled CP2K. Report bugs to compiler
vendors; they (and we) have an interest in fixing them.
Always run a 'make -j test' (See point 5.) after compilation to identifiy these problems.

==== 2d. BLAS and LAPACK (required, base functionality) ====
BLAS and LAPACK should be installed.  Using vendor-provided libraries
can make a very significant difference (up to 100%, e.g., ACML, MKL,
ESSL), not all optimized libraries are bug free. Use the latest versions available,
use the interfaces matching your compiler, and download all patches!

  * The canonical BLAS and LAPACK can be obtained from the Netlib repository.
    http://www.netlib.org/blas/
    http://www.netlib.org/lapack/ and see also
    http://www.netlib.org/lapack-dev/
  * Open fast alternatives, include:
    http://www.openblas.net/
    http://math-atlas.sourceforge.net/
    https://www.tacc.utexas.edu/research-development/tacc-software/gotoblas2

If compiling with OpenMP support then it is recommended to use a
non-threaded version of BLAS. In particular if compiling with MKL
and using OpenMP you must define -D__MKL to ensure the code is thread-safe.
MKL with multiple OpenMP threads in CP2K requires that CP2K was compiled
with the Intel compiler (and -D__INTEL_COMPILER is defined if explicit
pre-processing is performed using cpp instead of the compiler).

On the Mac, BLAS and LAPACK may be provided by Apple's Accelerate framework.
If using this framework, -D__ACCELERATE must be defined to account for some
interface incompatibilities between Accelerate and reference BLAS/LAPACK.

==== 2e. MPI and SCALAPACK (optional, required for MPI parallel builds) ====
MPI (version 2) and SCALAPACK are needed for parallel code.
(Use the latest versions available and download all patches!).
Note that your MPI installation must match the used Fortran compiler.
If your computing platform does not provide MPI, there are several freely
available alternatives:

  * MPICH2 MPI:  http://www-unix.mcs.anl.gov/mpi/mpich/
  * OpenMPI MPI: http://www.open-mpi.org/
  * ScaLAPACK: http://www.netlib.org/scalapack/ and see also
    http://www.netlib.org/lapack-dev/
    ScaLAPACK can be part of ACML or cluster MKL. These libraries are
    recommended if available. Recently a ScaLAPACK installer has been added
    that makes installing ScaLAPACK easier:
    http://www.netlib.org/scalapack/scalapack_installer.tgz

CP2K assumes that the MPI library implements MPI version 3.
If you have an older version of MPI (e.g. MPI 2.0) available
you must define -D__MPI_VERSION=2 in the arch file.

==== 2f. FFTW (optional, improved performance of FFTs) ====
FFTW can be used to improve FFT speed on a wide range of architectures.
It is strongly recommended to install and use FFTW3. The current version
of CP2K works with FFTW 3.X (use -D__FFTW3).
http://www.fftw.org/
Note that FFTW must know the Fortran compiler you will use in order to
install properly (e.g., ''export F77=gfortran'' before configure if you intend
to use gfortran).

Note that on machines and compilers which support SSE you can configure
FFTW3 with ''--enable-sse2''. Compilers/systems that do not align memory
(NAG f95, Intel IA32/gfortran) should either not use ''--enable-sse2''
or otherwise set the define -D__FFTW3_UNALIGNED in the arch file.
When building an OpenMP parallel version of CP2K (ssmp or psmp), the
FFTW3 threading library libfftw3_threads (or libfftw3_omp) is required.

==== 2g. LIBINT (optional, enables methods including HF exchange)  ====
Hartree-Fock exchange (optional, use -D__LIBINT) requires the libint
package to be installed.
Additional information can be found in
cp2k/tools/hfx_tools/libint_tools/README_LIBINT
Tested against libinit-1.1.4 and currently hardcoded to the default angular momentum LIBINT_MAX_AM 5
-D__LIBINT_MAX_AM and -D__LIBDERIV_MAX_AM1 can be used to change these defaults (see README_LIBINT).
(check your include/libint/libint.h to see if it matches)
-D__MAX_CONTR=4 (default=2) can be used to compile efficient contraction kernels up to l=4,
will take longer to compile.
http://sourceforge.net/projects/libint/files/v1-releases/libint-1.1.4.tar.gz/download
Note Do **NOT** use libinit-1.1.3, which was buggy.

==== 2h. libsmm (optional, improved performance for matrix multiplication) ====
  * A library for small matrix multiplies can be built from the included
    source (see tools/build_libsmm/README).  Usually only the double
    precision real and perhaps complex is needed.  Link to the generated
    libraries. For a couple of architectures prebuild libsmm are
    available at https://www.cp2k.org/static/downloads/libsmm/ .
  * Add -D__HAS_smm_dnn to the defines to make the code use the double
    precision real library.  Similarly use -D__HAS_smm_snn for single
    precision real and -D__HAS_smm_znn / -D__HAS_smm_cnn for
    double / single precision complex.
  * Add -D__HAS_smm_vec to enable the new vectorized interfaces of libsmm.

==== 2i. libxsmm (optional, improved performance for matrix multiplication) ====
  * A library for small matrix multiplications which is provided by Intel: https://github.com/hfp/libxsmm/
  * Add -D__LIBXSMM to enable it (with suitable include and library paths)
  * Tested with the released version 1.1.

==== 2j. CUDA (optional, improved performance on GPU systems) ====
  * -D__ACC needed to switch on the accelerator support
  * Use the -D__DBCSR_ACC to compile with accelerator support
    support for matrix multiplication.  For linking add -lcudart and -lrt
    to LIBS.
  * Use -D__PW_CUDA for CUDA support for PW (gather/scatter/fft)
    calculations.  The Fortran compiler must use an appended
    underscore for linking C subroutines. CUFFT 7.0 has a known bug and its use
    is disabled by default. NVidia's webpage list a patch (an upgraded version cufft i.e. >= 7.0.35)
    - use this together with -D__HAS_PATCHED_CUFFT_70.
  * USE -D__CUDA_PROFILING to turn on Nvidia Tools Extensions.
  * Link to a blas/scalapack library that accelerates large DGEMMs (e.g. libsci_acc)

==== 2k. libxc (optional, wider choice of xc functionals) ====
  * The version 4.0.3 (or later) of libxc needs to be downloaded
    (http://www.tddft.org/programs/octopus/wiki/index.php/Libxc) and installed.
    During the installation, the directory $(LIBXC_DIR)/lib and
    $(LIBXC_DIR)/include are created.
  * Note, the former deprecated flags -D__LIBXC2 and -D__LIBXC3 are ignored.
  * Add -D__LIBXC to DFLAGS, -I$(LIBXC_DIR)/include to FCFLAGS and
    -L$(LIBXC_DIR)/lib -lxcf03 -lxc to LIBS.

==== 2l. ELPA (optional, improved performance for diagonalization) ====
Library ELPA for the solution of the eigenvalue problem
  * ELPA replaces the ScaLapack SYEVD to improve the performance of the diagonalization
  * A version of ELPA can to be downloaded (http://elpa.rzg.mpg.de/software or directly
    http://elpa.rzg.mpg.de/elpa-tar-archive ).
  * During the installation the libelpa.a (or libelpa_mt.a if omp active) is created.
  * Add -D__ELPA=YYYYMM to DFLAGS, where YYYYMM denotes the release date of the library.
  * Currently supported versions are: 201112, 201308, 201311, 201406, 201502, 201505,
    201511, 201605, and 201611.
  * Add -I$(ELPA_INCLUDE_DIR)/modules to FCFLAGS
  * Add -I$(ELPA_INCLUDE_DIR)/elpa to FCFLAGS
  * Add -L$(ELPA_DIR) to LDFLAGS
  * Add -lelpa to LIBS
  * For specific architectures it can be better to install specifically
    optimized kernels (see BG) and/or employ a higher optimization level to compile it.

==== 2m. PEXSI (optional, low scaling SCF method) ====
The Pole EXpansion and Selected Inversion (PEXSI) method requires the PEXSI library
and two dependencies (ParMETIS or PT-Scotch and SuperLU_DIST).
  * Download PEXSI (www.pexsi.org) and install it and its dependencies by following
    the instructions in the README.md file distributed with PEXSI.
  * PEXSI versions 0.10.x have been tested with CP2K. Older versions are not supported.
  * PEXSI needs to be built with ''make finstall''.

In the arch file of CP2K:
  * Add ''-lpexsi_${SUFFIX} -llapack -lblas -lsuperlu_dist_3.3 -lparmetis -lmetis'', and their paths
    (with -L$(LIB_DIR)) to LIBS. It is important that a copy of LAPACK and BLAS is placed before and
    after these libraries  (replace -llapack and -lblas with the optimized versions as needed).
  * in order to link in PT-Scotch instead of ParMETIS replace ''-lparmetis -lmetis'' with:
      -lptscotchparmetis -lptscotch -lptscotcherr -lscotchmetis -lscotch -lscotcherr
  * Add ''-I$(PEXSI_DIR)/fortran/'' (for f_ppexsi_interface.mod) to FCFLAGS.
  * Add -D__LIBPEXSI to DFLAGS.

Below are some additional hints that may help in the compilation process:
  * For building PT-Scotch, the flag ''-DSCOTCH_METIS_PREFIX'' in
    Makefile.inc must not be set and the flag ''-DSCOTCH_PTHREAD'' must be removed.
  * For building SuperLU_DIST with PT-Scotch, you must set the following in make.inc.
      METISLIB = -lscotchmetis -lscotch -lscotcherr
      PARMETISLIB = -lptscotchparmetis -lptscotch -lptscotcherr

==== 2n. QUIP (optional, wider range of interaction potentials) ====
QUIP - QUantum mechanics and Interatomic Potentials
Support for QUIP can be enabled via the flag -D__QUIP .
For more information see http://www.libatoms.org/ .

==== 2o. PLUMED (optional, enables various enhanced sampling methods) ====
CP2K can be compiled with PLUMED 2.x (-D__PLUMED2).
Note that the code can only be built for one of these libraries at a time.

See https://cp2k.org/howto:install_with_plumed for full instructions.

==== 2p. spglib (optional, crystal symmetries tools) ====
A library for finding and handling crystal symmetries
  * The spglib can be downloaded from https://github.com/atztogo/spglib
  * For building CP2K with the spglib add -D__SPGLIB to DFLAGS

===== 3. Compile =====

==== 3a. ARCH files ====
The location of compiler and libraries needs to be specified. Examples
for a number of common architectures examples can be found in cp2k/arch/*.*
The names of these files match architecture.version (e.g., Linux-x86-64-gfortran.sopt).
Alternatively https://dashboard.cp2k.org/ provides sample arch files
as part of the testing reports (click on the status field, search for 'ARCH-file').

Conventionally, there are six versions:
^ Acronym ^        Meaning          ^       Recommended for        ^
| sdbg    | serial                  | single core testing and debugging        |
| sopt    | serial                  | general single core usage |
| ssmp    | parallel (only OpenMP)  | optimized, single node, multi core |
| pdbg    | parallel (only MPI)     | multinode testing and debugging |
| popt    | parallel (only MPI)     | general usage, no threads       |
| psmp    | parallel (MPI + OpenMP) | general usage, threading might improve scalability and memory usage |

You'll need to modify one of these files to match your system's settings.
You can now build CP2K using these settings (where -j N allows for a
parallel build using N processes):
  > cd cp2k/makefiles
  > make -j N ARCH=architecture VERSION=version
e.g.
  > make -j N ARCH=Linux-x86-64-gfortran VERSION=sopt
as a short-cut, you can build several version of the code at once
  > make -j N ARCH=Linux-x86-64-gfortran VERSION="sopt popt ssmp psmp"
An executable should appear in cp2k/exe/*

All compiled files, libraries, executables, .. of all architectures and
versions can be removed with
  > make distclean
To remove only objects and mod files (i.e., keep exe) for a given
ARCH/VERSION use, e.g.,
  > make ARCH=Linux-x86-64-gfortran VERSION=sopt clean
to remove everything for a given ARCH/VERSION use, e.g.,
  > make ARCH=Linux-x86-64-gfortran VERSION=sopt realclean

==== 3b. Compilation Flags ====

The following flags should be present (or not) in the arch file, partially depending on installed libraries (see 2.)
  * -D__parallel -D__SCALAPACK parallel runs
  * -D__LIBINT use libint (needed for HF exchange)
  * -D__LIBXC use libxc
  * -D__ELPA use ELPA in place of SYEVD  to solve the eigenvalue problem
  * -D__FFTW3 FFTW version 3 is recommended
  * -D__PW_CUDA CUDA FFT and associated gather/scatter on the GPU
  * -D__MKL link the MKL library for linear algebra and/or FFT

  * with -D__GRID_CORE=X (with X=1..6) specific optimized core routines can
    be selected.  Reasonable defaults are provided (see cp2k/src/grid/collocate_fast.f90)
    but trial-and-error might yield (a small ~10%) speedup.
  * with -D__HAS_LIBGRID (and -L/path/to/libgrid.a in LIBS) tuned versions of
    integrate and collocate routines can be generated.
    See cp2k/tools/autotune_grid/README for details
  * -D__PILAENV_BLOCKSIZE : can be used to specify the blocksize (e.g. -D__PILAENV_BLOCKSIZE=1024),
    which is a hack to overwrite (if the linker allows this) the PILAENV function provided by Scalapack.
    This can lead to much improved PDGEMM performance. The optimal value depends on hardware (GPU?) and precise problem.
    Alternatively, Cray provides an environment variable to this effect (e.g. export LIBSCI_ACC_PILAENV=4000)
  * -D__STATM_RESIDENT or -D__STATM_TOTAL toggles memory usage reporting between resident memory and total memory
  * -D__CRAY_PM_ACCEL_ENERGY or -D__CRAY_PM_ENERGY switch on energy profiling on Cray systems
  * -D__NO_ABORT to avoid calling abort, but STOP instead (useful for coverage testing, and to avoid core dumps on some systems)

Features useful to deal with legacy systems
  * -D__NO_MPI_THREAD_SUPPORT_CHECK  - Workaround for MPI libraries that do
    not declare they are thread safe (funneled) but you want to
    use them with OpenMP code anyways.
  * -D__HAS_NO_MPI_MOD - workaround if mpi has been built for a different (version
    of the) Fortran compiler, rendering the MPI module unreadable
    (reverts to f77 style mpif.h includes)
  * -D__NO_IPI_DRIVER disables the socket interface in case of troubles compiling
    on systems that do not support POSIX sockets
  * -D__HAS_NO_SHARED_GLIBC should be defined on systems where a shared glibc is
    not available at runtime for some reason e.g. on HPC systems
    where some file systems are not available on the compute nodes
  * -D__HAS_IEEE_EXCEPTIONS disables trapping temporarily for libraries like scalapack.
  * The Makefile automatically compiles in the path to the data directory via
    the flag -D__DATA_DIR. If you want to compile in a different path,
    set the variable DATA_DIR in your arch-file.
  * -D__HAS_NO_OMP_3 CP2K assumes that compilers support OpenMP 3.0.
    If this is not the case specify this flag to compile.
    Runtime performance will be poorer on low numbers of processors
  * -D__HAS_NO_CUDA_STREAM_PRIORITIES - Needed for CUDA sdk version < 5.5
  * -D__NO_STATM_ACCESS - Do not try to read from /proc/self/statm to
    get memory usage information. This is otherwise attempted on several
    Linux-based architectures or using with the NAG, gfortran, compilers.
  * -D__F2008 Allow for conformity check with the Fortran 2008 standard when using the GFortran compiler flag -std=f2008

===== 4. If it doesn't work? =====
If things fail, take a break... have ago back to 2a (or skip to step 6).

===== 5. Regtesting =====

If compilation works fine, it is recommended to test the generated binary,
to exclude errors in libraries, or miscompilations, etc.

make -j ARCH=... VERSION=... test

should work if you can locally execute CP2K without the need for e.g. batch submission.

In the other case, you might need to configure the underlying testing script as described more systematically at

https://www.cp2k.org/dev:regtesting

===== 6. Talk to us ====
In any case please tell us your comments, praise, criticism, thanks, ...
see https://www.cp2k.org/

===== 7. Manual =====
A reference manual of CP2K can be found on the web: https://manual.cp2k.org/
or can be generated using the cp2k executable, see
https://manual.cp2k.org/trunk/generate_manual_howto.html

===== 8. Happy computing! =====

 The CP2K team.