2. Getting Started¶

2.2.1. Read this first:¶

Building LIGGGHTS(R)-PUBLIC can be non-trivial. You may need to edit a makefile, there are compiler options to consider, additional libraries can be used (MPI, FFT, JPEG, PNG), LIGGGHTS(R)-PUBLIC packages may be included or excluded, some of these packages use auxiliary libraries which need to be pre-built, etc.

Please read this section carefully. If you are not comfortable with makefiles, or building codes on a Unix platform, or running an MPI job on your machine, please find a local expert to help you. Many compiling, linking, and run problems that users have are often not LIGGGHTS(R)-PUBLIC issues - they are peculiar to the user’s system, compilers, libraries, etc. Such questions are better answered by a local expert.

If you have a build problem that you are convinced is a LIGGGHTS(R)-PUBLIC issue (e.g. the compiler complains about a line of LIGGGHTS(R)-PUBLIC source code), then please post a question to the LIGGGHTS(R)-PUBLIC forum.

If you succeed in building LIGGGHTS(R)-PUBLIC on a new kind of machine, for which there isn’t a similar Makefile for in the src/MAKE directory, send it to the developers and we can include it in the LIGGGHTS(R)-PUBLIC distribution. In particular, we are interested in cases where Makefile.auto does not work, so that we can improve its performance.

2.2.2. Steps to build a LIGGGHTS(R)-PUBLIC executable:¶

With LIGGGHTS version 3.5.1 we have rolled out a all new and magic Makefile.auto which hopefully will make building LIGGGHTS as simple as possible. If the following steps do not work for you please see the advanced building description here.

Before attempting a build ensure that your system has all required prerequisites installed. A solid basis for several popular operating systems are listed below:

Ubuntu 16.04LTS:
  sudo apt-get install openmpi-bin libopenmpi-dev libvtk6.2 libvtk6-dev
-----
Ubuntu 17.10:
  sudo apt-get install openmpi-bin libopenmpi-dev libvtk6.3 libvtk6-dev
-----
Fedora 25:
  su -
  dnf install openmpi openmpi-devel paraview-openmpi paraview-openmpi-devel gcc-c++
  exit
  echo "export PATH=$PATH:/usr/lib64/openmpi/bin" >> ~/.bashrc
  echo "export LIBRARY_PATH=$LIBRARY_PATH:/usr/lib64/openmpi/lib:/usr/lib64/openmpi/lib/paraview" >> ~/.bashrc
  echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/lib64/openmpi/lib:/usr/lib64/openmpi/lib/paraview" >> ~/.bashrc
  echo "export C_INCLUDE_PATH=$C_INCLUDE_PATH:/usr/lib64/openmpi/include/paraview" >> ~/.bashrc
  echo "export CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/usr/lib64/openmpi/include/paraview" >> ~/.bashrc

Step 0

The src directory contains the C++ source and header files for LIGGGHTS(R)-PUBLIC. It also contains a top-level Makefile and a MAKE sub-directory with several Makefile.* files for many machines. From within the src directory, type “make” or “gmake”. You should see a list of available choices. Of particular interest is the auto option, as it should do all the heavy lifting for us. So start by typing

make auto

into the command line. If you are running this for the first time you will see the following message:

>>> WARNING <<<
Created MAKE/Makefile.user for the first time. Please check that the options
in that file are set correctly and run make again.

That is perfectly normal as MAKE/Makefile.user does not exist by default and contains some default options. The compilation will continue and if you are lucky enough it will actually produce an executable called lmp_auto in your src/ folder. If this is the case you are done and can move on to Running LIGGGHTS(R)-PUBLIC

Should the compilation interupt please carefully study the error message. The following procedure will explain how to set compilation variables for make auto.

Step 1

To configure these options open MAKE/Makefile.user with your favourite text editor. There are two sections in this file. The first one specifies which options and features in LIGGGHTS(R)-PUBLIC you would like to activate. The first three lines are related to MPI and read:

# MPI: "ON" or "OFF"
# Description: Use the message passing interface for parallel execution
USE_MPI = "ON"

The first, commented line indicates that either “ON” or “OFF” are valid parameters of the variable called USE_MPI. A short description of the option follows and the last line actually sets the option to “ON”. The default MAKE/Makefile.user comes with some sensibly set defaults. So you might not need to change anything at all.

The second part of this file is by default all commented out and deals with user and machine specific paths. Say that USE_VTK is set to “ON” and your VTK installation is not in your /usr path, but in /home/liggghts/vtk. In that case have a look at the following lines:

# VTK specific variables
#
# Path that contains the includes (vtkVersion.h)
#VTK_INC_USR=-I/path/to/vtk/include
# Path that contains the VTK libraries
#VTK_LIB_USR=-L/path/to/vtk/lib
# Additional VTK libraries to include
#VTK_ADDLIBS_USR=

In this case you would want to change VTK_INC_USR and VTK_LIB_USR so that they become

# VTK specific variables
#
# Path that contains the includes (vtkVersion.h)
VTK_INC_USR=-I/home/liggghts/vtk/include
# Path that contains the VTK libraries
VTK_LIB_USR=-L/home/liggghts/vtk/lib
# Additional VTK libraries to include
#VTK_ADDLIBS_USR=

Note that the two lines were uncommented and their values were changed as required. You can also see that include paths (normally containing INC in the variable name) need to be prefixed with -I and library paths (containing LIB) with -L. If you have non-standard paths, this can be a bit tricky to set up, so if you need any help ask a local expert that knows the setup of your machine.

If you run make auto the Makefile will automatically check if the options you have provided are valid. It will hopefully supply you with helpful error messages in case some options cannot be found.

Step 2

After all options are set to your satisfaction. Simply run

make auto

again to test the options and compile LIGGGHTS(R)-PUBLIC. After the compilation is finished you will obtain a executable name lmp_auto and you can continue here.

For most users it will be convenient if they are able to run LIGGGHTS(R)-PUBLIC by simply typing liggghts on the command line. To make this possible we need to create a symbolic link. So after the compilation is complete and your lmp_auto executable was created you can run the following command to create a system-wide link:

sudo ln -s lmp_auto /usr/local/bin

Since sudo is not available on all systems (e.g. Fedora) you can alternatively try:

su -c "ln -s lmp_auto /usr/local/bin"

Step 3 (Advanced usage)

Makefile.auto accepts up to two variables as additional input which are called debug and postfix. The former variable can be useful when debugging LIGGGHTS(R)-PUBLIC and can be used by typing

make auto debug=ON

The arguments that can be passed to the debug variable are “ON” and “FULL”. This has the same effect as changing the USE_DEBUG variable inside your Makefile.user to “ON” and “FULL”, respectively. I.e. with “ON” a optimized debug version of the code is produced, whereas with “FULL” a unoptimized version of the is compiled. The latter can be quite useful when using a debugger to look at the local variables inside a code fragment.

When using a debug variable the executables will be called either lmp_auto-debug or lmp_auto-fulldebug for “ON” and “FULL”, respectively.

The latter variable postfix can be used by typing

make auto postifx=myString

In this case Makefile.auto will not look for the MAKE/Makefile.user file, but MAKE/Makefile.user_myString. If it does not exist it will clone MAKE/Makefile.user (instead of a default template). The resulting executable will be called lmp_auto_myString (instead of lmp_auto).

The use of the postfix variable should not be required under normal development. It allows advanced developers to have executables with different features enabled or disabled and based upon the default Makefile.user.

All model combination of LIGGGHTS(R)-PUBLIC are automatically available starting with version 3.7. However, only a subset of them are compiled in an optimized manner. This might give you performance losses between 5 and 20%. In case you are using a model combination that is not optimized, LIGGGHTS(R)-PUBLIC will notify you of this. In this case you can create a file called style_contact_model_user.whitelist in your LIGGGHTS(R)-PUBLIC src/ folder and fill it with entries such as

GRAN_MODEL(HERTZ, TANGENTIAL_OFF, COHESION_OFF, ROLLING_OFF, SURFACE_DEFAULT)
GRAN_MODEL(HERTZ, TANGENTIAL_HISTORY, COHESION_OFF, ROLLING_EPSD, SURFACE_DEFAULT)

After creating or modifying such a file with the appropriate entries you will need to recompile LIGGGHTS(R)-PUBLIC and this time it will be built with optimized model combinations specified in this file.

In addition you can automatically scan files or folders recursively for LIGGGHTS(R)-PUBLIC input scripts and search them for their used contact model. With this list an addition to the whitelist is automatically created. Running the following commands within the LIGGGHTS(R)-PUBLIC src directory

./genAutoExamplesWhitelist.sh -h
./genAutoExamplesWhitelist.sh ../examples

The first will display the help message for genAutoExamplesWhitelist.sh. The second will recursively search the examples folder of your LIGGGHTS(R)-PUBLIC installation and scan all in.* files for the used contact models. It will also create the file style_contact_model_autoExamples.whitelist containing the unique used models in the whitelist format.

A third whitelist is automatically created during the compilation and is stored in style_contact_model.whitelist . If this file exists, the next compilation will NOT change this file. You can manually delete it and recreate it with

sh Make.sh models
sh Make.sh models_full

During every compilation the three whitelist files style_contact_model_user.whitelist , style_contact_model_autoExamples.whitelist and style_contact_model.whitelist are automatically merged and only unique entries are kept in the merged file.

2.2.3. Advanced building using custom makefiles¶

Step 0

The src directory contains the C++ source and header files for LIGGGHTS(R)-PUBLIC. It also contains a top-level Makefile and a MAKE sub-directory with low-level Makefile.* files for a few selected platforms. From within the src directory, type “make” or “gmake”. You should see a list of available choices. If one of those is the machine and options you want, you can type a command like:

make mpi
or
gmake serial

NOTE On a multi-processor or multi-core platform you can launch a parallel make, by using the “-j nprocessors” switch with the make command, which will build LIGGGHTS(R)-PUBLIC more quickly.

If you get no errors and an executable like lmp_mpi or lmp_serial is produced, you’re done; it’s your lucky day.

Note that by default only a few of LIGGGHTS(R)-PUBLIC optional packages are installed. To build LIGGGHTS(R)-PUBLIC with optional packages, see this section below.

Step 1

If Step 0 did not work, you will need to create a low-level Makefile for your machine, like Makefile.foo. You should make a copy of an existing src/MAKE/Makefile.* as a starting point. The only portions of the file you need to edit are the first line, the “compiler/linker settings” section, and the “LIGGGHTS(R)-PUBLIC-specific settings” section.

Step 2

Change the first line of src/MAKE/Makefile.foo to list the word “foo” after the “#”, and whatever other options it will set. This is the line you will see if you just type “make”.

Step 3

The “compiler/linker settings” section lists compiler and linker settings for your C++ compiler, including optimization flags. You can use g++, the open-source GNU compiler, which is available on all Unix systems. You can also use mpicc which will typically be available if MPI is installed on your system, though you should check which actual compiler it wraps. Vendor compilers often produce faster code. On boxes with Intel CPUs, we suggest using the commercial Intel icc compiler, which can be downloaded from Intel’s compiler site.

If building a C++ code on your machine requires additional libraries, then you should list them as part of the LIB variable.

The DEPFLAGS setting is what triggers the C++ compiler to create a dependency list for a source file. This speeds re-compilation when source (.cpp) or header (.h) files are edited. Some compilers do not support dependency file creation, or may use a different switch than -D. GNU g++ works with -D. If your compiler can’t create dependency files, then you’ll need to create a Makefile.foo patterned after Makefile.storm, which uses different rules that do not involve dependency files. Note that when you build LIGGGHTS(R)-PUBLIC for the first time on a new platform, a long list of *.d files will be printed out rapidly. This is not an error; it is the Makefile doing its normal creation of dependencies.

Step 4

The “system-specific settings” section has several parts. Note that if you change any -D setting in this section, you should do a full re-compile, after typing “make clean” (which will describe different clean options).

The LMP_INC variable is used to include options that turn on ifdefs within the LIGGGHTS(R)-PUBLIC code. The options that are currently recogized are:

• -DLAMMPS_GZIP
• -DLAMMPS_JPEG
• -DLAMMPS_PNG
• -DLAMMPS_FFMPEG
• -DLAMMPS_MEMALIGN
• -DLAMMPS_XDR
• -DLAMMPS_SMALLBIG
• -DLAMMPS_BIGBIG
• -DLAMMPS_SMALLSMALL
• -DLAMMPS_LONGLONG_TO_LONG
• -DPACK_ARRAY
• -DPACK_POINTER
• -DPACK_MEMCPY

The read_data and dump commands will read/write gzipped files if you compile with -DLAMMPS_GZIP. It requires that your machine supports the “popen” function in the standard runtime library and that a gzip executable can be found by LIGGGHTS(R)-PUBLIC during a run.

If you use -DLAMMPS_JPEG, the dump image command will be able to write out JPEG image files. For JPEG files, you must also link LIGGGHTS(R)-PUBLIC with a JPEG library, as described below. If you use -DLAMMPS_PNG, the dump image command will be able to write out PNG image files. For PNG files, you must also link LIGGGHTS(R)-PUBLIC with a PNG library, as described below. If neither of those two defines are used, LIGGGHTS(R)-PUBLIC will only be able to write out uncompressed PPM image files.

If you use -DLAMMPS_FFMPEG, the dump movie command will be available to support on-the-fly generation of rendered movies the need to store intermediate image files. It requires that your machines supports the “popen” function in the standard runtime library and that an FFmpeg executable can be found by LIGGGHTS(R)-PUBLIC during the run.

Using -DLAMMPS_MEMALIGN=<bytes> enables the use of the posix_memalign() call instead of malloc() when large chunks or memory are allocated by LIGGGHTS(R)-PUBLIC. This can help to make more efficient use of vector instructions of modern CPUS, since dynamically allocated memory has to be aligned on larger than default byte boundaries (e.g. 16 bytes instead of 8 bytes on x86 type platforms) for optimal performance.

If you use -DLAMMPS_XDR, the build will include XDR compatibility files for doing particle dumps in XTC format. This is only necessary if your platform does have its own XDR files available. See the Restrictions section of the dump command for details.

Use at most one of the -DLAMMPS_SMALLBIG, -DLAMMPS_BIGBIG, -D-DLAMMPS_SMALLSMALL settings. The default is -DLAMMPS_SMALLBIG. These settings refer to use of 4-byte (small) vs 8-byte (big) integers within LIGGGHTS(R)-PUBLIC, as specified in src/lmptype.h. The only reason to use the BIGBIG setting is to enable simulation of huge molecular systems with more than 2 billion atoms or to allow moving atoms to wrap back through a periodic box more than 512 times. The only reason to use the SMALLSMALL setting is if your machine does not support 64-bit integers. See the Additional build tips section below for more details.

The -DLAMMPS_LONGLONG_TO_LONG setting may be needed if your system or MPI version does not recognize “long long” data types. In this case a “long” data type is likely already 64-bits, in which case this setting will convert to that data type.

Using one of the -DPACK_ARRAY, -DPACK_POINTER, and -DPACK_MEMCPY options can make for faster parallel FFTs (in the PPPM solver) on some platforms. The -DPACK_ARRAY setting is the default. See the kspace_style command for info about PPPM. See Step 6 below for info about building LIGGGHTS(R)-PUBLIC with an FFT library.

Step 5

The 3 MPI variables are used to specify an MPI library to build LAMMPS with.

If you want LIGGGHTS(R)-PUBLIC to run in parallel, you must have an MPI library installed on your platform. If you use an MPI-wrapped compiler, such as “mpicc” to build LIGGGHTS(R)-PUBLIC, you should be able to leave these 3 variables blank; the MPI wrapper knows where to find the needed files. If not, and MPI is installed on your system in the usual place (under /usr/local), you also may not need to specify these 3 variables. On some large parallel machines which use “modules” for their compile/link environements, you may simply need to include the correct module in your build environment. Or the parallel machine may have a vendor-provided MPI which the compiler has no trouble finding.

Failing this, with these 3 variables you can specify where the mpi.h file (MPI_INC) and the MPI library file (MPI_PATH) are found and the name of the library file (MPI_LIB).

If you are installing MPI yourself, we recommend Argonne’s MPICH2 or OpenMPI. MPICH can be downloaded from the Argonne MPI site. OpenMPI can be downloaded from the OpenMPI site. Other MPI packages should also work. If you are running on a big parallel platform, your system people or the vendor should have already installed a version of MPI, which is likely to be faster than a self-installed MPICH or OpenMPI, so find out how to build and link with it. If you use MPICH or OpenMPI, you will have to configure and build it for your platform. The MPI configure script should have compiler options to enable you to use the same compiler you are using for the LIGGGHTS(R)-PUBLIC build, which can avoid problems that can arise when linking LIGGGHTS(R)-PUBLIC to the MPI library.

If you just want to run LIGGGHTS(R)-PUBLIC on a single processor, you can use the dummy MPI library provided in src/STUBS, since you don’t need a true MPI library installed on your system. See the src/MAKE/Makefile.serial file for how to specify the 3 MPI variables in this case. You will also need to build the STUBS library for your platform before making LIGGGHTS(R)-PUBLIC itself. To build from the src directory, type “make stubs”, or from the STUBS dir, type “make”. This should create a libmpi_stubs.a file suitable for linking to LIGGGHTS(R)-PUBLIC. If the build fails, you will need to edit the STUBS/Makefile for your platform.

The file STUBS/mpi.c provides a CPU timer function called MPI_Wtime() that calls gettimeofday() . If your system doesn’t support gettimeofday() , you’ll need to insert code to call another timer. Note that the ANSI-standard function clock() rolls over after an hour or so, and is therefore insufficient for timing long LIGGGHTS(R)-PUBLIC simulations.

Step 6

The 3 FFT variables allow you to specify an FFT library which LIGGGHTS(R)-PUBLIC uses (for performing 1d FFTs) when running the particle-particle particle-mesh (PPPM) option for long-range Coulombics via the kspace_style command.

LIGGGHTS(R)-PUBLIC supports various open-source or vendor-supplied FFT libraries for this purpose. If you leave these 3 variables blank, LIGGGHTS(R)-PUBLIC will use the open-source KISS FFT library, which is included in the LIGGGHTS(R)-PUBLIC distribution. This library is portable to all platforms and for typical LIGGGHTS(R)-PUBLIC simulations is almost as fast as FFTW or vendor optimized libraries. If you are not including the KSPACE package in your build, you can also leave the 3 variables blank.

Otherwise, select which kinds of FFTs to use as part of the FFT_INC setting by a switch of the form -DFFT_XXX. Recommended values for XXX are: MKL, SCSL, FFTW2, and FFTW3. Legacy options are: INTEL, SGI, ACML, and T3E. For backward compatability, using -DFFT_FFTW will use the FFTW2 library. Using -DFFT_NONE will use the KISS library described above.

You may also need to set the FFT_INC, FFT_PATH, and FFT_LIB variables, so the compiler and linker can find the needed FFT header and library files. Note that on some large parallel machines which use “modules” for their compile/link environements, you may simply need to include the correct module in your build environment. Or the parallel machine may have a vendor-provided FFT library which the compiler has no trouble finding.

FFTW is a fast, portable library that should also work on any platform. You can download it from www.fftw.org. Both the legacy version 2.1.X and the newer 3.X versions are supported as -DFFT_FFTW2 or -DFFT_FFTW3. Building FFTW for your box should be as simple as ./configure; make. Note that on some platforms FFTW2 has been pre-installed, and uses renamed files indicating the precision it was compiled with, e.g. sfftw.h, or dfftw.h instead of fftw.h. In this case, you can specify an additional define variable for FFT_INC called -DFFTW_SIZE, which will select the correct include file. In this case, for FFT_LIB you must also manually specify the correct library, namely -lsfftw or -ldfftw.

The FFT_INC variable also allows for a -DFFT_SINGLE setting that will use single-precision FFTs with PPPM, which can speed-up long-range calulations, particularly in parallel or on GPUs. Fourier transform and related PPPM operations are somewhat insensitive to floating point truncation errors and thus do not always need to be performed in double precision. Using the -DFFT_SINGLE setting trades off a little accuracy for reduced memory use and parallel communication costs for transposing 3d FFT data. Note that single precision FFTs have only been tested with the FFTW3, FFTW2, MKL, and KISS FFT options.

Step 7

The 3 JPG variables allow you to specify a JPEG and/or PNG library which LIGGGHTS(R)-PUBLIC uses when writing out JPEG or PNG files via the dump image command. These can be left blank if you do not use the -DLAMMPS_JPEG or -DLAMMPS_PNG switches discussed above in Step 4, since in that case JPEG/PNG output will be disabled.

A standard JPEG library usually goes by the name libjpeg.a or libjpeg.so and has an associated header file jpeglib.h. Whichever JPEG library you have on your platform, you’ll need to set the appropriate JPG_INC, JPG_PATH, and JPG_LIB variables, so that the compiler and linker can find it.

A standard PNG library usually goes by the name libpng.a or libpng.so and has an associated header file png.h. Whichever PNG library you have on your platform, you’ll need to set the appropriate JPG_INC, JPG_PATH, and JPG_LIB variables, so that the compiler and linker can find it.

As before, if these header and library files are in the usual place on your machine, you may not need to set these variables.

Step 8

Note that by default only a few of LIGGGHTS(R)-PUBLIC optional packages are installed. To build LIGGGHTS(R)-PUBLIC with optional packages, see this section below, before proceeding to Step 9.

Step 9

That’s it. Once you have a correct Makefile.foo, you have installed the optional LIGGGHTS(R)-PUBLIC packages you want to include in your build, and you have pre-built any other needed libraries (e.g. MPI, FFT, package libraries), all you need to do from the src directory is type something like this:

make foo
or
gmake foo

You should get the executable lmp_foo when the build is complete.

2.2.4. Errors that can occur when making LIGGGHTS(R)-PUBLIC:¶

Here are two non-obvious errors that can occur:

(1) If the make command breaks immediately with errors that indicate it can’t find files with a “*” in their names, this can be because your machine’s native make doesn’t support wildcard expansion in a makefile. Try gmake instead of make. If that doesn’t work, try using a -f switch with your make command to use a pre-generated Makefile.list which explicitly lists all the needed files, e.g.

make makelist
make -f Makefile.list linux
gmake -f Makefile.list mac

The first “make” command will create a current Makefile.list with all the file names in your src dir. The 2nd “make” command (make or gmake) will use it to build LIGGGHTS(R)-PUBLIC. Note that you should include/exclude any desired optional packages before using the “make makelist” command.

(2) If you get an error that says something like ‘identifier “atoll” is undefined’, then your machine does not support “long long” integers. Try using the -DLAMMPS_LONGLONG_TO_LONG setting described above in Step 4.

2.2.5. Additional build tips:¶

1. Building LIGGGHTS(R)-PUBLIC for multiple platforms.

You can make LIGGGHTS(R)-PUBLIC for multiple platforms from the same src directory. Each target creates its own object sub-directory called Obj_target where it stores the system-specific *.o files.

2. Cleaning up.

Typing “make clean-all” or “make clean-machine” will delete *.o object files created when LIGGGHTS(R)-PUBLIC is built, for either all builds or for a particular machine.

(3) Changing the LIGGGHTS(R)-PUBLIC size limits via -DLAMMPS_SMALLBIG or -DLAMMPS_BIBIG or -DLAMMPS_SMALLSMALL

As explained above, any of these 3 settings can be specified on the LMP_INC line in your low-level src/MAKE/Makefile.foo.

The default is -DLAMMPS_SMALLBIG which allows for systems with up to 2^63 atoms and timesteps (about 9 billion billion). The atom limit is for atomic systems that do not require atom IDs. For molecular models, which require atom IDs, the limit is 2^31 atoms (about 2 billion). With this setting, image flags are stored in 32-bit integers, which means for 3 dimensions that atoms can only wrap around a periodic box at most 512 times. If atoms move through the periodic box more than this limit, the image flags will “roll over”, e.g. from 511 to -512, which can cause diagnostics like the mean-squared displacement, as calculated by the compute msd command, to be faulty.

To allow for larger molecular systems or larger image flags, compile with -DLAMMPS_BIGBIG. This enables molecular systems with up to 2^63 atoms (about 9 billion billion). And image flags will not “roll over” until they reach 2^20 = 1048576.

If your system does not support 8-byte integers, you will need to compile with the -DLAMMPS_SMALLSMALL setting. This will restrict your total number of atoms (for atomic or molecular models) and timesteps to 2^31 (about 2 billion). Image flags will roll over at 2^9 = 512.

Note that in src/lmptype.h there are also settings for the MPI data types associated with the integers that store atom IDs and total system sizes. These need to be consistent with the associated C data types, or else LIGGGHTS(R)-PUBLIC will generate a run-time error.

In all cases, the size of problem that can be run on a per-processor basis is limited by 4-byte integer storage to 2^31 atoms per processor (about 2 billion). This should not normally be a restriction since such a problem would have a huge per-processor memory footprint due to neighbor lists and would run very slowly in terms of CPU secs/timestep.

2.2.6. Building for a Mac:¶

OS X is BSD Unix, so it should just work. Try using “make auto” or use “make serial” as fallback. This is untested but feel free to give us feedback on cfdem.com

2.2.7. Building for Windows:¶

The recommened way to do this is using CMake and Visual Studio. Install CMake and launch the associated GUI. Point the Where is your source code: input to your src/ folder and set the build folder to some folder (recommended: make a build folder in your LIGGGHTS(R)-PUBLIC-base directory). Press Configure to get your system settings. You will most likely have to set the VTK_DIR option to the folder in which you built the VTK library. Once this is done press Configure again until all errors are reolved so that you can Generate the project. After that you should be able to press Open Project to open Visual Studio where you can build LIGGGHTS(R)-PUBLIC.

The other way to do this is install and use cygwin to build LIGGGHTS(R)-PUBLIC with a standard Linux make, just as you would on any Linux box. Your cygwin environment will need several packages such as cmake, g++, gcc, openmpi, make. Note that when compiling VTK you need to disable all rendering related VTK options as OpenGL won’t be available. Note that this is an option that should only be used by advanced users.

2.5.1. Static library:¶

To build LIGGGHTS(R)-PUBLIC as a static library (*.a file on Linux), type

make makelib
make -f Makefile.lib foo

where foo is the machine name (if you normally compile with auto then use this option). This kind of library is typically used to statically link a driver application to LIGGGHTS(R)-PUBLIC, so that you can insure all dependencies are satisfied at compile time. Note that inclusion or exclusion of any desired optional packages should be done before typing “make makelib”. The first “make” command will create a current Makefile.lib with all the file names in your src dir. The second “make” command will use it to build LIGGGHTS(R)-PUBLIC as a static library, using the ARCHIVE and ARFLAGS settings in src/MAKE/Makefile.foo. The build will create the file liblammps_foo.a which another application can link to.

2.5.2. Shared library:¶

To build LIGGGHTS(R)-PUBLIC as a shared library (*.so file on Linux), which can be dynamically loaded, e.g. from Python, type

make makeshlib
make -f Makefile.shlib foo

where foo is the machine name (if you normally compile with auto then use this option). This kind of library is required when wrapping LIGGGHTS(R)-PUBLIC with Python; see Section_python for details. Again, note that inclusion or exclusion of any desired optional packages should be done before typing “make makelib”. The first “make” command will create a current Makefile.shlib with all the file names in your src dir. The second “make” command will use it to build LIGGGHTS(R)-PUBLIC as a shared library, using the SHFLAGS and SHLIBFLAGS settings in src/MAKE/Makefile.foo. The build will create the file liblammps_foo.so which another application can link to dyamically. It will also create a soft link liblammps.so, which the Python wrapper uses by default.

Note that for a shared library to be usable by a calling program, all the auxiliary libraries it depends on must also exist as shared libraries. This will be the case for libraries included with LIGGGHTS(R)-PUBLIC, such as the dummy MPI library in src/STUBS or any package libraries in lib/packges, since they are always built as shared libraries with the -fPIC switch. However, if a library like MPI or FFTW does not exist as a shared library, the second make command will generate an error. This means you will need to install a shared library version of the package. The build instructions for the library should tell you how to do this.

As an example, here is how to build and install the MPICH library, a popular open-source version of MPI, distributed by Argonne National Labs, as a shared library in the default /usr/local/lib location:

./configure --enable-shared
make
make install

You may need to use “sudo make install” in place of the last line if you do not have write privileges for /usr/local/lib. The end result should be the file /usr/local/lib/libmpich.so.

2.5.3. Additional requirement for using a shared library:¶

The operating system finds shared libraries to load at run-time using the environment variable LD_LIBRARY_PATH. So you may wish to copy the file src/liblammps.so or src/liblammps_g++.so (for example) to a place the system can find it by default, such as /usr/local/lib, or you may wish to add the LIGGGHTS(R)-PUBLIC src directory to LD_LIBRARY_PATH, so that the current version of the shared library is always available to programs that use it.

For the csh or tcsh shells, you would add something like this to your ~/.cshrc file:

setenv LD_LIBRARY_PATH $*LD_LIBRARY_PATH*:/home/sjplimp/lammps/src

2.5.4. Calling the LIGGGHTS(R)-PUBLIC library:¶

Either flavor of library (static or shared0 allows one or more LIGGGHTS(R)-PUBLIC objects to be instantiated from the calling program.

When used from a C++ program, all of LIGGGHTS(R)-PUBLIC is wrapped in a LAMMPS_NS namespace; you can safely use any of its classes and methods from within the calling code, as needed.

When used from a C or Fortran program or a scripting language like Python, the library has a simple function-style interface, provided in src/library.cpp and src/library.h.

See the sample codes in examples/COUPLE/simple for examples of C++ and C and Fortran codes that invoke LIGGGHTS(R)-PUBLIC thru its library interface. There are other examples as well in the COUPLE directory which are discussed in Section_howto 10 of the manual. See Section_python of the manual for a description of the Python wrapper provided with LIGGGHTS(R)-PUBLIC that operates through the LIGGGHTS(R)-PUBLIC library interface.

The files src/library.cpp and library.h define the C-style API for using LIGGGHTS(R)-PUBLIC as a library. See Section_howto 19 of the manual for a description of the interface and how to extend it for your needs.