3.7. Packages with extra build options
When building with some packages, additional steps may be required, in addition to:
-D PKG_NAME=yes # CMake
make yes-name # make
as described on the Build_package doc page.
For a CMake build there may be additional optional or required variables to set. For a build with make, a provided library under the lammps/lib directory may need to be built first. Or an external library may need to exist on your system or be downloaded and built. You may need to tell LAMMPS where it is found on your system.
This is the list of packages that may require additional steps.
3.7.1. COMPRESS package
To build with this package you must have the zlib compression library available on your system.
CMake build:
If CMake cannot find the library, you can set these variables:
-D ZLIB_INCLUDE_DIR=path # path to zlib.h header file
-D ZLIB_LIBRARIES=path # path to libz.a (.so) file
Traditional make:
If make cannot find the library, you can edit the lib/compress/Makefile.lammps file to specify the paths and library name.
3.7.2. GPU package
To build with this package, you must choose options for precision and which GPU hardware to build for.
CMake build:
-D GPU_API=value # value = opencl (default) or cuda
-D GPU_PREC=value # precision setting
# value = double or mixed (default) or single
-D OCL_TUNE=value # hardware choice for GPU_API=opencl
# generic (default) or intel (Intel CPU) or fermi, kepler, cypress (NVIDIA)
-D GPU_ARCH=value # primary GPU hardware choice for GPU_API=cuda
# value = sm_XX, see below
# default is Cuda-compiler dependent, but typically sm_20
-D CUDPP_OPT=value # optimization setting for GPU_API=cuda
# enables CUDA Performance Primitives Optimizations
# yes (default) or no
GPU_ARCH settings for different GPU hardware is as follows:
- sm_12 or sm_13 for GT200 (supported by CUDA 3.2 until CUDA 6.5)
- sm_20 or sm_21 for Fermi (supported by CUDA 3.2 until CUDA 7.5)
- sm_30 or sm_35 or sm_37 for Kepler (supported since CUDA 5)
- sm_50 or sm_52 for Maxwell (supported since CUDA 6)
- sm_60 or sm_61 for Pascal (supported since CUDA 8)
- sm_70 for Volta (supported since CUDA 9)
- sm_75 for Turing (supported since CUDA 10)
A more detailed list can be found, for example, at Wikipedia’s CUDA article
CMake can detect which version of the CUDA toolkit is used and thus can include support for all major GPU architectures supported by this toolkit. Thus the GPU_ARCH setting is merely an optimization, to have code for the preferred GPU architecture directly included rather than having to wait for the JIT compiler of the CUDA driver to translate it.
Traditional make:
Before building LAMMPS, you must build the GPU library in lib/gpu. You can do this manually if you prefer; follow the instructions in lib/gpu/README. Note that the GPU library uses MPI calls, so you must use the same MPI library (or the STUBS library) settings as the main LAMMPS code. This also applies to the -DLAMMPS_BIGBIG, -DLAMMPS_SMALLBIG, or -DLAMMPS_SMALLSMALL settings in whichever Makefile you use.
You can also build the library in one step from the lammps/src dir, using a command like these, which simply invoke the lib/gpu/Install.py script with the specified args:
make lib-gpu # print help message
make lib-gpu args="-b" # build GPU library with default Makefile.linux
make lib-gpu args="-m xk7 -p single -o xk7.single" # create new Makefile.xk7.single, altered for single-precision
make lib-gpu args="-m mpi -a sm_60 -p mixed -b" # build GPU library with mixed precision and P100 using other settings in Makefile.mpi
Note that this procedure starts with a Makefile.machine in lib/gpu, as specified by the “-m” switch. For your convenience, machine makefiles for “mpi” and “serial” are provided, which have the same settings as the corresponding machine makefiles in the main LAMMPS source folder. In addition you can alter 4 important settings in the Makefile.machine you start from via the corresponding -c, -a, -p, -e switches (as in the examples above), and also save a copy of the new Makefile if desired:
- CUDA_HOME = where NVIDIA CUDA software is installed on your system
- CUDA_ARCH = sm_XX, what GPU hardware you have, same as CMake GPU_ARCH above
- CUDA_PRECISION = precision (double, mixed, single)
- EXTRAMAKE = which Makefile.lammps.* file to copy to Makefile.lammps
The file Makefile.linux_multi is set up to include support for multiple GPU architectures as supported by the CUDA toolkit in use. This is done through using the “–gencode ” flag, which can be used multiple times and thus support all GPU architectures supported by your CUDA compiler.
If the library build is successful, 3 files should be created: lib/gpu/libgpu.a, lib/gpu/nvc_get_devices, and lib/gpu/Makefile.lammps. The latter has settings that enable LAMMPS to link with CUDA libraries. If the settings in Makefile.lammps for your machine are not correct, the LAMMPS build will fail, and lib/gpu/Makefile.lammps may need to be edited.
Note
If you re-build the GPU library in lib/gpu, you should always un-install the GPU package in lammps/src, then re-install it and re-build LAMMPS. This is because the compilation of files in the GPU package uses the library settings from the lib/gpu/Makefile.machine used to build the GPU library.
3.7.3. KIM package
To build with this package, the KIM library must be downloaded and built on your system. It must include the KIM models that you want to use with LAMMPS.
Note that in LAMMPS lingo, a KIM model driver is a pair style (e.g. EAM or Tersoff). A KIM model is a pair style for a particular element or alloy and set of parameters, e.g. EAM for Cu with a specific EAM potential file. Also note that installing the KIM API library with all its models, may take around 30 min to build. Of course you only need to do that once.
See the list of KIM model drivers here: https://openkim.org/kim-items/model-drivers/alphabetical
See the list of all KIM models here: https://openkim.org/kim-items/models/by-model-drivers
See the list of example KIM models included by default here: https://openkim.org/kim-api on the “What is in the KIM API source package?” page.
CMake build:
-D DOWNLOAD_KIM=value # download OpenKIM API v1 for build, value = no (default) or yes
-D KIM_LIBRARY=path # KIM library file (only needed if a custom location)
-D KIM_INCLUDE_DIR=path # KIM include directory (only needed if a custom location)
If DOWNLOAD_KIM is set, the KIM library will be downloaded and built inside the CMake build directory. If the KIM library is already on your system (in a location CMake cannot find it), KIM_LIBRARY is the filename (plus path) of the KIM library file, not the directory the library file is in. KIM_INCLUDE_DIR is the directory the KIM include file is in.
Traditional make:
You can download and build the KIM library manually if you prefer; follow the instructions in lib/kim/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/kim/Install.py script with the specified args.
make lib-kim # print help message
make lib-kim args="-b " # (re-)install KIM API lib with only example models
make lib-kim args="-b -a Glue_Ercolessi_Adams_Al__MO_324507536345_001" # ditto plus one model
make lib-kim args="-b -a everything" # install KIM API lib with all models
make lib-kim args="-n -a EAM_Dynamo_Ackland_W__MO_141627196590_002" # add one model or model driver
make lib-kim args="-p /usr/local/kim-api" # use an existing KIM API installation at the provided location
make lib-kim args="-p /usr/local/kim-api -a EAM_Dynamo_Ackland_W__MO_141627196590_002" # ditto but add one model or driver
3.7.4. KOKKOS package
To build with this package, you must choose which hardware you want to build for, either CPUs (multi-threading via OpenMP) or KNLs (OpenMP) or GPUs (NVIDIA Cuda).
For a CMake or make build, these are the possible choices for the KOKKOS_ARCH settings described below. Note that for CMake, these are really Kokkos variables, not LAMMPS variables. Hence you must use case-sensitive values, e.g. BDW, not bdw.
- ARMv80 = ARMv8.0 Compatible CPU
- ARMv81 = ARMv8.1 Compatible CPU
- ARMv8-ThunderX = ARMv8 Cavium ThunderX CPU
- BGQ = IBM Blue Gene/Q CPUs
- Power8 = IBM POWER8 CPUs
- Power9 = IBM POWER9 CPUs
- SNB = Intel Sandy/Ivy Bridge CPUs
- HSW = Intel Haswell CPUs
- BDW = Intel Broadwell Xeon E-class CPUs
- SKX = Intel Sky Lake Xeon E-class HPC CPUs (AVX512)
- KNC = Intel Knights Corner Xeon Phi
- KNL = Intel Knights Landing Xeon Phi
- Kepler30 = NVIDIA Kepler generation CC 3.0
- Kepler32 = NVIDIA Kepler generation CC 3.2
- Kepler35 = NVIDIA Kepler generation CC 3.5
- Kepler37 = NVIDIA Kepler generation CC 3.7
- Maxwell50 = NVIDIA Maxwell generation CC 5.0
- Maxwell52 = NVIDIA Maxwell generation CC 5.2
- Maxwell53 = NVIDIA Maxwell generation CC 5.3
- Pascal60 = NVIDIA Pascal generation CC 6.0
- Pascal61 = NVIDIA Pascal generation CC 6.1
CMake build:
For multicore CPUs using OpenMP, set these 2 variables.
-D KOKKOS_ARCH=archCPU # archCPU = CPU from list above
-D KOKKOS_ENABLE_OPENMP=yes
For Intel KNLs using OpenMP, set these 2 variables:
-D KOKKOS_ARCH=KNL
-D KOKKOS_ENABLE_OPENMP=yes
For NVIDIA GPUs using CUDA, set these 4 variables:
-D KOKKOS_ARCH="archCPU;archGPU" # archCPU = CPU from list above that is hosting the GPU
# archGPU = GPU from list above
-D KOKKOS_ENABLE_CUDA=yes
-D KOKKOS_ENABLE_OPENMP=yes
-D CMAKE_CXX_COMPILER=wrapper # wrapper = full path to Cuda nvcc wrapper
The wrapper value is the Cuda nvcc compiler wrapper provided in the Kokkos library: lib/kokkos/bin/nvcc_wrapper. The setting should include the full path name to the wrapper, e.g.
-D CMAKE_CXX_COMPILER=/home/username/lammps/lib/kokkos/bin/nvcc_wrapper
Traditional make:
Choose which hardware to support in Makefile.machine via KOKKOS_DEVICES and KOKKOS_ARCH settings. See the src/MAKE/OPTIONS/Makefile.kokkos* files for examples.
For multicore CPUs using OpenMP:
KOKKOS_DEVICES = OpenMP
KOKKOS_ARCH = archCPU # archCPU = CPU from list above
For Intel KNLs using OpenMP:
KOKKOS_DEVICES = OpenMP
KOKKOS_ARCH = KNL
For NVIDIA GPUs using CUDA:
KOKKOS_DEVICES = Cuda
KOKKOS_ARCH = archCPU,archGPU # archCPU = CPU from list above that is hosting the GPU
# archGPU = GPU from list above
For GPUs, you also need these 2 lines in your Makefile.machine before the CC line is defined, in this case for use with OpenMPI mpicxx. The 2 lines define a nvcc wrapper compiler, which will use nvcc for compiling CUDA files and use a C++ compiler for non-Kokkos, non-CUDA files.
KOKKOS_ABSOLUTE_PATH = $(shell cd $(KOKKOS_PATH); pwd)
export OMPI_CXX = $(KOKKOS_ABSOLUTE_PATH)/config/nvcc_wrapper
CC = mpicxx
3.7.5. LATTE package
To build with this package, you must download and build the LATTE library.
CMake build:
-D DOWNLOAD_LATTE=value # download LATTE for build, value = no (default) or yes
-D LATTE_LIBRARY=path # LATTE library file (only needed if a custom location)
If DOWNLOAD_LATTE is set, the LATTE library will be downloaded and built inside the CMake build directory. If the LATTE library is already on your system (in a location CMake cannot find it), LATTE_LIBRARY is the filename (plus path) of the LATTE library file, not the directory the library file is in.
Traditional make:
You can download and build the LATTE library manually if you prefer; follow the instructions in lib/latte/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invokes the lib/latte/Install.py script with the specified args:
make lib-latte # print help message
make lib-latte args="-b" # download and build in lib/latte/LATTE-master
make lib-latte args="-p $HOME/latte" # use existing LATTE installation in $HOME/latte
make lib-latte args="-b -m gfortran" # download and build in lib/latte and
# copy Makefile.lammps.gfortran to Makefile.lammps
Note that 3 symbolic (soft) links, “includelink” and “liblink” and “filelink.o”, are created in lib/latte to point into the LATTE home dir. When LAMMPS itself is built it will use these links. You should also check that the Makefile.lammps file you create is appropriate for the compiler you use on your system to build LATTE.
3.7.6. MEAM package
Note
the use of the MEAM package is discouraged, as it has been superseded by the USER-MEAMC package, which is a direct translation of the Fortran code in the MEAM library to C++. The code in USER-MEAMC should be functionally equivalent to the MEAM package, fully supports use of pair_style hybrid (the MEAM package does not), and has optimizations that make it significantly faster than the MEAM package.
CMake build:
No additional settings are needed besides “-D PKG_MEAM=yes”.
Traditional make:
Before building LAMMPS, you must build the MEAM library in lib/meam. You can build the MEAM library manually if you prefer; follow the instructions in lib/meam/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/meam/Install.py script with the specified args:
make lib-meam # print help message
make lib-meam args="-m mpi" # build with default Fortran compiler compatible with your MPI library
make lib-meam args="-m serial" # build with compiler compatible with "make serial" (GNU Fortran)
make lib-meam args="-m ifort" # build with Intel Fortran compiler using Makefile.ifort
Note
You should test building the MEAM library with both the Intel and GNU compilers to see if a simulation runs faster with one versus the other on your system.
The build should produce two files: lib/meam/libmeam.a and lib/meam/Makefile.lammps. The latter is copied from an existing Makefile.lammps.* and has settings needed to link C++ (LAMMPS) with Fortran (MEAM library). Typically the two compilers used for LAMMPS and the MEAM library need to be consistent (e.g. both Intel or both GNU compilers). If necessary, you can edit/create a new lib/meam/Makefile.machine file for your system, which should define an EXTRAMAKE variable to specify a corresponding Makefile.lammps.machine file.
3.7.7. MESSAGE package
This package can optionally include support for messaging via sockets, using the open-source ZeroMQ library, which must be installed on your system.
CMake build:
-D MESSAGE_ZMQ=value # build with ZeroMQ support, value = no (default) or yes
Traditional make:
Before building LAMMPS, you must build the CSlib library in lib/message. You can build the CSlib library manually if you prefer; follow the instructions in lib/message/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/message/Install.py script with the specified args:
make lib-message # print help message make lib-message args=”-m -z” # build with MPI and socket (ZMQ) support make lib-message args=”-s” # build as serial lib with no ZMQ support
The build should produce two files: lib/message/cslib/src/libmessage.a and lib/message/Makefile.lammps. The latter is copied from an existing Makefile.lammps.* and has settings to link with the ZeroMQ library if requested in the build.
3.7.8. MSCG package
To build with this package, you must download and build the MS-CG library. Building the MS-CG library and using it from LAMMPS requires a C++11 compatible compiler and that the GSL (GNU Scientific Library) headers and libraries are installed on your machine. See the lib/mscg/README and MSCG/Install files for more details.
CMake build:
-D DOWNLOAD_MSCG=value # download MSCG for build, value = no (default) or yes
-D MSCG_LIBRARY=path # MSCG library file (only needed if a custom location)
-D MSCG_INCLUDE_DIR=path # MSCG include directory (only needed if a custom location)
If DOWNLOAD_MSCG is set, the MSCG library will be downloaded and built inside the CMake build directory. If the MSCG library is already on your system (in a location CMake cannot find it), MSCG_LIBRARY is the filename (plus path) of the MSCG library file, not the directory the library file is in. MSCG_INCLUDE_DIR is the directory the MSCG include file is in.
Traditional make:
You can download and build the MS-CG library manually if you prefer; follow the instructions in lib/mscg/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/mscg/Install.py script with the specified args:
make lib-mscg # print help message
make lib-mscg args="-b -m serial" # download and build in lib/mscg/MSCG-release-master
# with the settings compatible with "make serial"
make lib-mscg args="-b -m mpi" # download and build in lib/mscg/MSCG-release-master
# with the settings compatible with "make mpi"
make lib-mscg args="-p /usr/local/mscg-release" # use the existing MS-CG installation in /usr/local/mscg-release
Note that 2 symbolic (soft) links, “includelink” and “liblink”, will be created in lib/mscg to point to the MS-CG src/installation dir. When LAMMPS is built in src it will use these links. You should not need to edit the lib/mscg/Makefile.lammps file.
3.7.9. OPT package
CMake build:
No additional settings are needed besides “-D PKG_OPT=yes”.
Traditional make:
The compile flag “-restrict” must be used to build LAMMPS with the OPT package when using Intel compilers. It should be added to the CCFLAGS line of your Makefile.machine. See src/MAKE/OPTIONS/Makefile.opt for an example.
3.7.10. POEMS package
CMake build:
No additional settings are needed besides “-D PKG_OPT=yes”.
Traditional make:
Before building LAMMPS, you must build the POEMS library in lib/poems. You can do this manually if you prefer; follow the instructions in lib/poems/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/poems/Install.py script with the specified args:
make lib-poems # print help message
make lib-poems args="-m serial" # build with GNU g++ compiler (settings as with "make serial")
make lib-poems args="-m mpi" # build with default MPI C++ compiler (settings as with "make mpi")
make lib-poems args="-m icc" # build with Intel icc compiler
The build should produce two files: lib/poems/libpoems.a and lib/poems/Makefile.lammps. The latter is copied from an existing Makefile.lammps.* and has settings needed to build LAMMPS with the POEMS library (though typically the settings are just blank). If necessary, you can edit/create a new lib/poems/Makefile.machine file for your system, which should define an EXTRAMAKE variable to specify a corresponding Makefile.lammps.machine file.
3.7.11. PYTHON package
Building with the PYTHON package requires you have a Python shared library available on your system, which needs to be a Python 2 version, 2.6 or later. Python 3 is not yet supported. See lib/python/README for more details.
CMake build:
-D PYTHON_EXECUTABLE=path # path to Python executable to use
Without this setting, CMake will guess the default Python on your system. To use a different Python version, you can either create a virtualenv, activate it and then run cmake. Or you can set the PYTHON_EXECUTABLE variable to specify which Python interpreter should be used. Note note that you will also need to have the development headers installed for this version, e.g. python2-devel.
Traditional make:
The build uses the lib/python/Makefile.lammps file in the compile/link process to find Python. You should only need to create a new Makefile.lammps.* file (and copy it to Makefile.lammps) if the LAMMPS build fails.
3.7.12. VORONOI package
To build with this package, you must download and build the Voro++ library.
CMake build:
-D DOWNLOAD_VORO=value # download Voro++ for build, value = no (default) or yes
-D VORO_LIBRARY=path # Voro++ library file (only needed if at custom location)
-D VORO_INCLUDE_DIR=path # Voro++ include directory (only needed if at custom location)
If DOWNLOAD_VORO is set, the Voro++ library will be downloaded and built inside the CMake build directory. If the Voro++ library is already on your system (in a location CMake cannot find it), VORO_LIBRARY is the filename (plus path) of the Voro++ library file, not the directory the library file is in. VORO_INCLUDE_DIR is the directory the Voro++ include file is in.
Traditional make:
You can download and build the Voro++ library manually if you prefer; follow the instructions in lib/voronoi/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/voronoi/Install.py script with the specified args:
make lib-voronoi # print help message
make lib-voronoi args="-b" # download and build the default version in lib/voronoi/voro++-<version>
make lib-voronoi args="-p $HOME/voro++" # use existing Voro++ installation in $HOME/voro++
make lib-voronoi args="-b -v voro++0.4.6" # download and build the 0.4.6 version in lib/voronoi/voro++-0.4.6
Note that 2 symbolic (soft) links, “includelink” and “liblink”, are created in lib/voronoi to point to the Voro++ src dir. When LAMMPS builds in src it will use these links. You should not need to edit the lib/voronoi/Makefile.lammps file.
3.7.13. USER-ATC package
The USER-ATC package requires the MANYBODY package also be installed.
CMake build:
No additional settings are needed besides “-D PKG_USER-ATC=yes” and “-D PKG_MANYBODY=yes”.
Traditional make:
Before building LAMMPS, you must build the ATC library in lib/atc. You can do this manually if you prefer; follow the instructions in lib/atc/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/atc/Install.py script with the specified args:
make lib-atc # print help message
make lib-atc args="-m serial" # build with GNU g++ compiler and MPI STUBS (settings as with "make serial")
make lib-atc args="-m mpi" # build with default MPI compiler (settings as with "make mpi")
make lib-atc args="-m icc" # build with Intel icc compiler
The build should produce two files: lib/atc/libatc.a and lib/atc/Makefile.lammps. The latter is copied from an existing Makefile.lammps.* and has settings needed to build LAMMPS with the ATC library. If necessary, you can edit/create a new lib/atc/Makefile.machine file for your system, which should define an EXTRAMAKE variable to specify a corresponding Makefile.lammps.machine file.
Note that the Makefile.lammps file has settings for the BLAS and LAPACK linear algebra libraries. As explained in lib/atc/README these can either exist on your system, or you can use the files provided in lib/linalg. In the latter case you also need to build the library in lib/linalg with a command like these:
make lib-linalg # print help message
make lib-linalg args="-m serial" # build with GNU Fortran compiler (settings as with "make serial")
make lib-linalg args="-m mpi" # build with default MPI Fortran compiler (settings as with "make mpi")
make lib-linalg args="-m gfortran" # build with GNU Fortran compiler
3.7.14. USER-AWPMD package
CMake build:
No additional settings are needed besides “-D PKG_USER-AQPMD=yes”.
Traditional make:
Before building LAMMPS, you must build the AWPMD library in lib/awpmd. You can do this manually if you prefer; follow the instructions in lib/awpmd/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/awpmd/Install.py script with the specified args:
make lib-awpmd # print help message
make lib-awpmd args="-m serial" # build with GNU g++ compiler and MPI STUBS (settings as with "make serial")
make lib-awpmd args="-m mpi" # build with default MPI compiler (settings as with "make mpi")
make lib-awpmd args="-m icc" # build with Intel icc compiler
The build should produce two files: lib/awpmd/libawpmd.a and lib/awpmd/Makefile.lammps. The latter is copied from an existing Makefile.lammps.* and has settings needed to build LAMMPS with the AWPMD library. If necessary, you can edit/create a new lib/awpmd/Makefile.machine file for your system, which should define an EXTRAMAKE variable to specify a corresponding Makefile.lammps.machine file.
Note that the Makefile.lammps file has settings for the BLAS and LAPACK linear algebra libraries. As explained in lib/awpmd/README these can either exist on your system, or you can use the files provided in lib/linalg. In the latter case you also need to build the library in lib/linalg with a command like these:
make lib-linalg # print help message
make lib-linalg args="-m serial" # build with GNU Fortran compiler (settings as with "make serial")
make lib-linalg args="-m mpi" # build with default MPI Fortran compiler (settings as with "make mpi")
make lib-linalg args="-m gfortran" # build with GNU Fortran compiler
3.7.15. USER-COLVARS package
CMake build:
No additional settings are needed besides “-D PKG_USER-COLVARS=yes”.
Traditional make:
Before building LAMMPS, you must build the COLVARS library in lib/colvars. You can do this manually if you prefer; follow the instructions in lib/colvars/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/colvars/Install.py script with the specified args:
make lib-colvars # print help message
make lib-colvars args="-m serial" # build with GNU g++ compiler (settings as with "make serial")
make lib-colvars args="-m mpi" # build with default MPI compiler (settings as with "make mpi")
make lib-colvars args="-m g++-debug" # build with GNU g++ compiler and colvars debugging enabled
The build should produce two files: lib/colvars/libcolvars.a and lib/colvars/Makefile.lammps. The latter is copied from an existing Makefile.lammps.* and has settings needed to build LAMMPS with the COLVARS library (though typically the settings are just blank). If necessary, you can edit/create a new lib/colvars/Makefile.machine file for your system, which should define an EXTRAMAKE variable to specify a corresponding Makefile.lammps.machine file.
3.7.16. USER-PLUMED package
Before building LAMMPS with this package, you must first build PLUMED. PLUMED can be built as part of the LAMMPS build or installed separately from LAMMPS using the generic plumed installation instructions.
PLUMED can be linked into MD codes in three different modes: static, shared, and runtime. With the “static” mode, all the code that PLUMED requires is linked statically into LAMMPS. LAMMPS is then fully independent from the PLUMED installation, but you have to rebuild/relink it in order to update the PLUMED code inside it. With the “shared” linkage mode, LAMMPS is linked to a shared library that contains the PLUMED code. This library should preferably be installed in a globally accessible location. When PLUMED is linked in this way the same library can be used by multiple MD packages. Furthermore, the PLUMED library LAMMPS uses can be updated without the need for a recompile of LAMMPS for as long as the shared PLUMED library is ABI-compatible.
The third linkage mode is “runtime” which allows the user to specify which PLUMED kernel should be used at runtime by using the PLUMED_KERNEL environment variable. This variable should point to the location of the libplumedKernel.so dynamical shared object, which is then loaded at runtime. This mode of linking is particularly convenient for doing PLUMED development and comparing multiple PLUMED versions as these sorts of comparisons can be done without recompiling the hosting MD code. All three linkage modes are supported by LAMMPS on selected operating systems (e.g. Linux) and using either CMake or traditional make build. The “static” mode should be the most portable, while the “runtime” mode support in LAMMPS makes the most assumptions about operating system and compiler environment. If one mode does not work, try a different one, switch to a different build system, consider a global PLUMED installation or consider downloading PLUMED during the LAMMPS build.
CMake build:
When the “-D PKG_USER-PLUMED” flag is included in the cmake command you must ensure that GSL is installed in locations that are specified in your environment. There are then two additional commands that control the manner in which PLUMED is obtained and linked into LAMMPS.
-D DOWNLOAD_PLUMED=value # download PLUMED for build, value = no (default) or yes
-D PLUMED_MODE=value # Linkage mode for PLUMED, value = static (default), shared, or runtime
If DOWNLOAD_PLUMED is set to “yes”, the PLUMED library will be downloaded (the version of PLUMED that will be downloaded is hard-coded to a vetted version of PLUMED, usually a recent stable release version) and built inside the CMake build directory. If DOWNLOAD_PLUMED is set to “no” (the default), CMake will try to detect and link to an installed version of PLUMED. For this to work, the PLUMED library has to be installed into a location where the pkg-config tool can find it or the PKG_CONFIG_PATH environment variable has to be set up accordingly. PLUMED should be installed in such a location if you compile it using the default make; make install commands.
The PLUMED_MODE setting determines the linkage mode for the PLUMED library. The allowed values for this flag are “static” (default), “shared”, or “runtime”. For a discussion of PLUMED linkage modes, please see above. When DOWNLOAD_PLUMED is enabled the static linkage mode is recommended.
Traditional make:
PLUMED needs to be installed before the USER-PLUMED package is installed so that LAMMPS can find the right settings when compiling and linking the LAMMPS executable. You can either download and build PLUMED inside the LAMMPS plumed library folder or use a previously installed PLUMED library and point LAMMPS to its location. You also have to choose the linkage mode: “static” (default), “shared” or “runtime”. For a discussion of PLUMED linkage modes, please see above.
Download/compilation/configuration of the plumed library can be done from the src folder through the following make args:
make lib-plumed # print help message
make lib-plumed args="-b" # download and build PLUMED in lib/plumed/plumed2
make lib-plumed args="-p $HOME/.local" # use existing PLUMED installation in $HOME/.local
make lib-plumed args="-p /usr/local -m shared" # use existing PLUMED installation in
# /usr/local and use shared linkage mode
Note that 2 symbolic (soft) links, “includelink” and “liblink” are created in lib/plumed that point to the location of the PLUMED build to use. A new file lib/plumed/Makefile.lammps is also created with settings suitable for LAMMPS to compile and link PLUMED using the desired linkage mode. After this step is completed, you can install the USER-PLUMED package and compile LAMMPS in the usual manner:
make yes-user-plumed
make machine
Once this compilation completes you should be able to run LAMMPS in the usual way. For shared linkage mode, libplumed.so must be found by the LAMMPS executable, which on many operating systems means, you have to set the LD_LIBRARY_PATH environment variable accordingly.
Support for the different linkage modes in LAMMPS varies for different operating systems, using the static linkage is expected to be the most portable, and thus set to be the default.
If you want to change the linkage mode, you have to re-run “make lib-plumed” with the desired settings and do a re-install if the USER-PLUMED package with “make yes-user-plumed” to update the required makefile settings with the changes in the lib/plumed folder.
3.7.17. USER-H5MD package
To build with this package you must have the HDF5 software package installed on your system, which should include the h5cc compiler and the HDF5 library.
CMake build:
No additional settings are needed besides “-D PKG_USER-H5MD=yes”.
This should auto-detect the H5MD library on your system. Several advanced CMake H5MD options exist if you need to specify where it is installed. Use the ccmake (terminal window) or cmake-gui (graphical) tools to see these options and set them interactively from their user interfaces.
Traditional make:
Before building LAMMPS, you must build the CH5MD library in lib/h5md. You can do this manually if you prefer; follow the instructions in lib/h5md/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/h5md/Install.py script with the specified args:
make lib-h5md # print help message
make lib-hm5d args="-m h5cc" # build with h5cc compiler
The build should produce two files: lib/h5md/libch5md.a and lib/h5md/Makefile.lammps. The latter is copied from an existing Makefile.lammps.* and has settings needed to build LAMMPS with the system HDF5 library. If necessary, you can edit/create a new lib/h5md/Makefile.machine file for your system, which should define an EXTRAMAKE variable to specify a corresponding Makefile.lammps.machine file.
3.7.18. USER-INTEL package
To build with this package, you must choose which hardware you want to build for, either Intel CPUs or Intel KNLs. You should also typically install the USER-OMP package, as it can be used in tandem with the USER-INTEL package to good effect, as explained on the Speed intel doc page.
CMake build:
-D INTEL_ARCH=value # value = cpu (default) or knl
-D BUILD_OMP=yes # also required to build with the USER-INTEl package
Requires an Intel compiler as well as the Intel TBB and MKL libraries.
Traditional make:
Choose which hardware to compile for in Makefile.machine via the following settings. See src/MAKE/OPTIONS/Makefile.intel_cpu* and Makefile.knl files for examples.
For CPUs:
OPTFLAGS = -xHost -O2 -fp-model fast=2 -no-prec-div -qoverride-limits -qopt-zmm-usage=high
CCFLAGS = -g -qopenmp -DLAMMPS_MEMALIGN=64 -no-offload -fno-alias -ansi-alias -restrict $(OPTFLAGS)
LINKFLAGS = -g -qopenmp $(OPTFLAGS)
LIB = -ltbbmalloc
For KNLs:
OPTFLAGS = -xMIC-AVX512 -O2 -fp-model fast=2 -no-prec-div -qoverride-limits
CCFLAGS = -g -qopenmp -DLAMMPS_MEMALIGN=64 -no-offload -fno-alias -ansi-alias -restrict $(OPTFLAGS)
LINKFLAGS = -g -qopenmp $(OPTFLAGS)
LIB = -ltbbmalloc
3.7.19. USER-MOLFILE package
CMake build:
No additional settings are needed besides “-D PKG_USER-MOLFILE=yes”.
Traditional make:
The lib/molfile/Makefile.lammps file has a setting for a dynamic loading library libdl.a that is typically present on all systems. It is required for LAMMPS to link with this package. If the setting is not valid for your system, you will need to edit the Makefile.lammps file. See lib/molfile/README and lib/molfile/Makefile.lammps for details.
3.7.20. USER-NETCDF package
To build with this package you must have the NetCDF library installed on your system.
CMake build:
No additional settings are needed besides “-D PKG_USER-NETCDF=yes”.
This should auto-detect the NETCDF library if it is installed on your system at standard locations. Several advanced CMake NETCDF options exist if you need to specify where it was installed. Use the ccmake (terminal window) or cmake-gui (graphical) tools to see these options and set them interactively from their user interfaces.
Traditional make:
The lib/netcdf/Makefile.lammps file has settings for NetCDF include and library files which LAMMPS needs to build with this package. If the settings are not valid for your system, you will need to edit the Makefile.lammps file. See lib/netcdf/README for details.
3.7.21. USER-OMP package
CMake build:
No additional settings are required besides “-D PKG_USER-OMP=yes”. If CMake detects OpenMP support, the USER-OMP code will be compiled with multi-threading support enabled, otherwise as optimized serial code.
Traditional make:
To enable multi-threading support in the USER-OMP package (and other styles supporting OpenMP) the following compile and link flags must be added to your Makefile.machine file. See src/MAKE/OPTIONS/Makefile.omp for an example.
CCFLAGS: -fopenmp # for GNU Compilers
CCFLAGS: -qopenmp -restrict # for Intel compilers on Linux
LINKFLAGS: -fopenmp # for GNU Compilers
LINKFLAGS: -qopenmp # for Intel compilers on Linux
For other platforms and compilers, please consult the documentation about OpenMP support for your compiler.
3.7.22. USER-QMMM package
Note
The LAMMPS executable these steps produce is not yet functional for a QM/MM simulation. You must also build Quantum ESPRESSO and create a new executable (pwqmmm.x) which links LAMMPS and Quantum ESPRESSO together. These are steps 3 and 4 described in the lib/qmmm/README file. Unfortunately, the Quantum ESPRESSO developers have been breaking the interface that the QM/MM code in LAMMPS is using, so that currently (Summer 2018) using this feature requires either correcting the library interface feature in recent Quantum ESPRESSO releases, or using an outdated version of QE. The last version of Quantum ESPRESSO known to work with this QM/MM interface was version 5.4.1 from 2016.
CMake build:
The CMake build system currently does not support building the full QM/MM-capable hybrid executable of LAMMPS and QE called pwqmmm.x. You must use the traditional make build for this package.
Traditional make:
Before building LAMMPS, you must build the QMMM library in lib/qmmm. You can do this manually if you prefer; follow the first two steps explained in lib/qmmm/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/qmmm/Install.py script with the specified args:
make lib-qmmm # print help message
make lib-qmmm args="-m serial" # build with GNU Fortran compiler (settings as in "make serial")
make lib-qmmm args="-m mpi" # build with default MPI compiler (settings as in "make mpi")
make lib-qmmm args="-m gfortran" # build with GNU Fortran compiler
The build should produce two files: lib/qmmm/libqmmm.a and lib/qmmm/Makefile.lammps. The latter is copied from an existing Makefile.lammps.* and has settings needed to build LAMMPS with the QMMM library (though typically the settings are just blank). If necessary, you can edit/create a new lib/qmmm/Makefile.machine file for your system, which should define an EXTRAMAKE variable to specify a corresponding Makefile.lammps.machine file.
You can then install QMMM package and build LAMMPS in the usual manner. After completing the LAMMPS build and compiling Quantum ESPRESSO with external library support, go back to the lib/qmmm folder and follow the instructions on the README file to build the combined LAMMPS/QE QM/MM executable (pwqmmm.x) in the lib/qmmm folder.
3.7.23. USER-QUIP package
To build with this package, you must download and build the QUIP library. It can be obtained from GitHub. For support of GAP potentials, additional files with specific licensing conditions need to be downloaded and configured. See step 1 and step 1.1 in the lib/quip/README file for details on how to do this.
CMake build:
-D QUIP_LIBRARIES=path # path to libquip.a (only needed if a custom location)
CMake will not download and build the QUIP library. But once you have done that, a CMake build of LAMMPS with “-D PKG_USER-QUIP=yes” should work. Set QUIP_LIBRARIES if CMake cannot find the QUIP library.
Traditional make:
The download/build procedure for the QUIP library, described in lib/quip/README file requires setting two environment variables, QUIP_ROOT and QUIP_ARCH. These are accessed by the lib/quip/Makefile.lammps file which is used when you compile and link LAMMPS with this package. You should only need to edit Makefile.lammps if the LAMMPS build can not use its settings to successfully build on your system.
3.7.24. USER-SCAFACOS package
To build with this package, you must download and build the ScaFaCoS Coulomb solver library
CMake build:
-D DOWNLOAD_SCAFACOS=value # download ScaFaCoS for build, value = no (default) or yes
-D SCAFACOS_LIBRARY=path # ScaFaCos library file (only needed if at custom location)
-D SCAFACOS_INCLUDE_DIR=path # ScaFaCoS include directory (only needed if at custom location)
If DOWNLOAD_SCAFACOS is set, the ScaFaCoS library will be downloaded and built inside the CMake build directory. If the ScaFaCoS library is already on your system (in a location CMake cannot find it), SCAFACOS_LIBRARY is the filename (plus path) of the ScaFaCoS library file, not the directory the library file is in. SCAFACOS_INCLUDE_DIR is the directory the ScaFaCoS include file is in.
Traditional make:
You can download and build the ScaFaCoS library manually if you prefer; follow the instructions in lib/scafacos/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/scafacos/Install.py script with the specified args:
make lib-scafacos # print help message make lib-scafacos args=”-b” # download and build in lib/scafacos/scafacos-<version> make lib-scafacos args=”-p $HOME/scafacos # use existing ScaFaCoS installation in $HOME/scafacos
Note that 2 symbolic (soft) links, “includelink” and “liblink”, are created in lib/scafacos to point to the ScaFaCoS src dir. When LAMMPS builds in src it will use these links. You should not need to edit the lib/scafacos/Makefile.lammps file.
3.7.25. USER-SMD package
To build with this package, you must download the Eigen3 library. Eigen3 is a template library, so you do not need to build it.
CMake build:
-D DOWNLOAD_EIGEN3 # download Eigen3, value = no (default) or yes
-D EIGEN3_INCLUDE_DIR=path # path to Eigen library (only needed if a custom location)
If DOWNLOAD_EIGEN3 is set, the Eigen3 library will be downloaded and inside the CMake build directory. If the Eigen3 library is already on your system (in a location CMake cannot find it), EIGEN3_INCLUDE_DIR is the directory the Eigen3++ include file is in.
Traditional make:
You can download the Eigen3 library manually if you prefer; follow the instructions in lib/smd/README. You can also do it in one step from the lammps/src dir, using a command like these, which simply invoke the lib/smd/Install.py script with the specified args:
make lib-smd # print help message
make lib-smd args="-b" # download to lib/smd/eigen3
make lib-smd args="-p /usr/include/eigen3" # use existing Eigen installation in /usr/include/eigen3
Note that a symbolic (soft) link named “includelink” is created in lib/smd to point to the Eigen dir. When LAMMPS builds it will use this link. You should not need to edit the lib/smd/Makefile.lammps file.
3.7.26. USER-VTK package
To build with this package you must have the VTK library installed on your system.
CMake build:
No additional settings are needed besides “-D PKG_USER-VTK=yes”.
This should auto-detect the VTK library if it is installed on your system at standard locations. Several advanced VTK options exist if you need to specify where it was installed. Use the ccmake (terminal window) or cmake-gui (graphical) tools to see these options and set them interactively from their user interfaces.
Traditional make:
The lib/vtk/Makefile.lammps file has settings for accessing VTK files and its library, which LAMMPS needs to build with this package. If the settings are not valid for your system, check if one of the other lib/vtk/Makefile.lammps.* files is compatible and copy it to Makefile.lammps. If none of the provided files work, you will need to edit the Makefile.lammps file. See lib/vtk/README for details.