For users, the preferred method is to download a release. For developers, the preferred method is to download from Git.
For more details on downloading CP2K, see https://www.cp2k.org/download.
The most convenient way to install pre-requisites is by using the toolchain script.
For a complete introduction to the toolchain script, see the README for users or the README for developers.
The basic steps are:
- Read toolchain installation options:
> cd tools/toolchain/
> ./install_cp2k_toolchain.sh --help
- Launch toolchain script (example option choice)
> ./install_cp2k_toolchain.sh --with-libxsmm=install --with-openblas=system \
--with-fftw=system --with-reflapack=no --enable-cuda --enable-omp
- Once the script has completed successfully, follow the instructions given at the end of its output. Note that the pre-built arch files provided by the toolchain are for the GNU compiler, users have to adapt them for other compilers. It is possible to use the provided arch files as guidance.
Sub-points here discuss prerequisites needed to build CP2K. Copies of the recommended versions of 3rd party software can be downloaded from https://www.cp2k.org/static/downloads/.
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.
Python 2.7 or 3.5+ is needed to run the dependency generator. On most system Python is already installed. For more information visit: https://www.python.org/
A Fortran 2008 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. A list of tested compiler can be found here. Always run a make -j test
(See point 5.) after compilation to identify these problems.
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:
- Open fast alternatives, include:
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. If the cpp
precompiler is used in a separate precompilation step in combination with the Intel Fortran compiler, -D__INTEL_COMPILER
must be added explicitly (the Intel compiler sets __INTEL_COMPILER
otherwise automatically).
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.
When building on/for Windows using the Minimalist GNU for Windows (MinGW) environment, you must set -D__MINGW
, -D__NO_STATM_ACCESS
and -D__NO_IPI_DRIVER
to avoid undefined references during linking, respectively errors while printing the statistics.
MPI (version 2) and SCALAPACK are needed for parallel code. (Use the latest versions available and download all patches!).
- MPICH2 MPI: http://www-unix.mcs.anl.gov/mpi/mpich/
- OpenMPI MPI: http://www.open-mpi.org/
- ScaLAPACK:
- http://www.netlib.org/scalapack/
- 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 simplifies the installation.
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.
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
). It can be downloaded from http://www.fftw.org/
export F77=gfortran
before configure if you intend to use gfortran).
--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.
- Hartree-Fock exchange (optional, use
-D__LIBINT
) requires the libint package to be installed. - Recommended way to build libint: Download a CP2K-configured libint library from libint-cp2k. Build and install libint by following the instructions provided there. Note that using a library configured for higher maximum angular momentum will increase build time and binary size of CP2K executable (assuming static linking).
- CP2K is not hardwired to these provided libraries and any other libint library (version >= 2.5.0) should be compatible as long as it was compiled with
--enable-eri=1
and default ordering. - Avoid debugging information (
-g
flag) for compiling libint since this will increase library size by a large factor. - In the arch file of CP2K: add
-D__LIBINT
to theDFLAGS
. Add-L$(LIBINT_DIR)/lib -lint2 -lstdc++
toLIBS
and-I$(LIBINT_DIR)/include
toFCFLAGS
.lstdc++
is needed if you use the GNU C++ compiler. - Libint 1 is no longer supported and the previously needed flags
-D__LIBINT_MAX_AM
and-D__LIBDERIV_MAX_AM1
are ignored. -D__MAX_CONTR=4
(default=2) can be used to compile efficient contraction kernels up to l=4, but the build time will increase accordingly.
- 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 prebuilt 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.
- A library for matrix operations and deep learning primitives: https://github.com/hfp/libxsmm/
- Add
-D__LIBXSMM
to enable it (with suitable include and library paths)
-D__ACC
needed to enable accelerator support.- Use the
-D__DBCSR_ACC
to enable accelerator support for matrix multiplications. - Add
-lcudart -lrt -lnvrtc
to LIBS. - Specify the GPU type (e.g.
GPUVER = P100
) - Specify the C++ compiler (e.g.
CXX = g++
). Remember to set the flags to support C++11 standard. - Use
-D__PW_CUDA
for CUDA support for PW (gather/scatter/fft) calculations. - CUFFT 7.0 has a known bug and is therefore 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)
- The version 4.0.3 (or later) of libxc can be downloaded from http://www.tddft.org/programs/octopus/wiki/index.php/Libxc.
- During the installation, the directories
$(LIBXC_DIR)/lib
and$(LIBXC_DIR)/include
are created. - Add
-D__LIBXC
to DFLAGS,-I$(LIBXC_DIR)/include
to FCFLAGS and-L$(LIBXC_DIR)/lib -lxcf03 -lxc
to LIBS. ⚠️ Note that the deprecated flags-D__LIBXC2
and-D__LIBXC3
are ignored.
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 from http://elpa.rzg.mpg.de/software.
- During the installation the
libelpa.a
(orlibelpa_openmp.a
if OpenMP is enabled) is created. - Minimal supported version of ELPA is 2018.05.001.
- Add
-D__ELPA
toDFLAGS
- Add
-I$(ELPA_INCLUDE_DIR)/modules
toFCFLAGS
- Add
-I$(ELPA_INCLUDE_DIR)/elpa
toFCFLAGS
- Add
-L$(ELPA_DIR)
toLDFLAGS
- Add
-lelpa
toLIBS
- For specific architectures it can be better to install specifically optimized kernels (see BG) and/or employ a higher optimization level to compile it.
The Pole EXpansion and Selected Inversion (PEXSI) method requires the PEXSI library and two dependencies (ParMETIS or PT-Scotch and SuperLU_DIST).
- Download PEXSI (www.pexsi.org) and install it and its dependencies by following its README.md.
- PEXSI versions 0.10.x have been tested with CP2K. Older versions are not supported.
- PEXSI needs to be built with
make finstall
.
In the arch file of CP2K:
- Add
-lpexsi_${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/
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
inMakefile.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
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/ .
CP2K can be compiled with PLUMED 2.x (-D__PLUMED2
).
See https://cp2k.org/howto:install_with_plumed for full instructions.
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
SIRIUS is a domain specific library for electronic structure calculations.
- The code is available at https://github.com/electronic-structure/SIRIUS
- For building CP2K with SIRIUS add
-D__SIRIUS
to DFLAGS. - See https://electronic-structure.github.io/SIRIUS/ for more information.
- Use
-D__PW_FPGA
to enable FPGA support for PW (fft) calculations. Currently tested only for Intel Stratix 10 and Arria 10 GX1150 FPGAs. - Supports single precision and double precision fft calculations with the use of dedicated APIs.
- Double precision is the default API chosen when set using the
-D__PW_FPGA
flag. - Single precision can be set using an additional
-D__PW_FPGA_SP
flag along with the-D__PW_FPGA
flag. - Kernel code has to be synthesized separately and copied to a specific location.
- See https://github.com/pc2/fft3d-fpga for the kernel code and instructions for synthesis.
- Read
src/pw/fpga/README.md
for information on the specific location to copy the binaries to. - Currently supported FFT3d sizes - 16^3, 32^3, 64^3.
- Include aocl compile flags and
-D__PW_FPGA -D__PW_FPGA_SP
toCFLAGS
, aocl linker flags toLDFLAGS
and aocl libs toLIBS
. - CUDA and FPGA are mutually exclusive. Building with both
__PW_CUDA
and__PW_FPGA
will throw a compilation error.
The location of compiler and libraries needs to be specified. Examples for a number of common architectures examples can be found in arch folder. 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').
- With -DNDEBUG assertions may be stripped ("compiled out").
- NDEBUG is the ANSI-conforming symbol name (not __NDEBUG).
- Regular release builds may carry assertions for safety.
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) | multi-node 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):
> 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 the ./exe/
folder.
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
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 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. -
-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_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 variableDATA_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__CHECK_DIAG
Debug option which activates an orthonormality check of the eigenvectors calculated by the selected eigensolver
You can build CP2K for use as a library by adding libcp2k
as an option to your make
command, e.g.
> make -j N ARCH=Linux-x86-64-gfortran VERSION=sopt libcp2k
This will create libcp2k.a
in the relevant subdirectory of ./lib/
. You will need to add this subdirectory to the library search path of your compiler (typically via the LD_LIBRARY_PATH
environment variable or the -L
option to your compiler) and link to the library itself with -lcp2k
.
In order to use the functions in the library you will also require the libcp2k.h
header file. This can be found in ./src/start/
directory. You should add this directory to the header search path of your compiler (typically via the CPATH
environment variable or the -I
option to your compiler).
For Fortran users, you will require the module interface file (.mod
file) for every MODULE encountered in the source. These are compiler specific and are to be found in the subdirectory of ./obj/
that corresponds to your build, e.g.,
./obj/Linux-x86-64-gfortran/sopt/
In order for your compiler to find these, you will need to indicate their location to the compiler as is done for header files (typically via the CPATH
environment variable or the -I
option to your compiler).
If things fail, take a break... go back to 2a (or skip to step 6).
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
In any case please tell us your comments, praise, criticism, thanks,... see https://www.cp2k.org/
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
The CP2K team.