VASPml library

VASPml is a C++ library accompanying VASP, providing functionality related to machine-learned force fields. It is supposed to extend, and eventually replace, the original Fortran machine learning code inside VASP. Currently, it does not yet offer any training capabilities but rather focuses on inference. At this point VASPml is in a beta-testing stage and provides its first application, an interface to the popular molecular dynamics (MD) software LAMMPS. This allows users to combine VASP-generated machine-learned force fields with the large amount of MD-related features provided by LAMMPS, some of which may not be offered in VASP directly.

Build instructions

In future the source of VASPml will be distributed as part of the official VASP release. The build process of VASP will include the steps necessary to compile and link also the VASPml library and interfaces. However, at this point (and most likely even when integrated into VASP) it is possible to build VASPml completely independent of VASP. The following sections describe details of such an independent build of VASPml.

Prerequisites

1. VASPml requires a C++ compiler conforming to the C++17 language standard, for example compilers which are part of:
   • GNU Compiler Collection
   • Intel oneAPI Base Toolkit
   • NVIDIA HPC SDK
   • NEC SDK
2. Numerical libraries: LAPACK and BLAS, which are distributed for example as part of:
   • OpenBLAS
   • Intel oneAPI Math Kernel Library (part of Base Toolkit)
   • NVIDIA HPC SDK
   • NEC NLC (NEC Numeric Library Collection)
3. An MPI (Message Passing Interface) implementation, e.g. in
   • OpenMPI
   • Intel MPI (part of Intel oneAPI HPC Toolkit)
   • NVIDIA HPC SDK (OpenMPI)
   • NEC MPI

Build library and applications

Similar to VASP also VASPml requires to enter compiler details and library paths into a file named makefile.include before the build process can be started. Template files for this file can be found in the arch subdirectory. Usually it is convenient to start from one of these files. Hence, first copy it to the base directory and rename it to makefile.include, e.g.

cp arch/makefile.include.gnu makefile.include

Then modify the contents to reflect the compiler and library settings on your machine, for details see the compiler and linker options section below. Once done, the VASPml library can be built by executing this command in the top directory:

make -j 

This will automatically build the two targets libvaspml and applications, and is equivalent of running two make commands explicitly in this order:

make libvaspml -j
make applications -j

The libvaspml target builds the library with same name and places it in the lib folder. The applications target compiles and links standalone applications present in src/applications. At the moment there is only one application named vaspml-predict which predicts energy, forces and stress for one POSCAR file with a given ML_FF force field file. The executable will be copied to the bin directory.

With the -j flag present make will run the build process in parallel, starting as many parallel jobs as possible. You can limit the maximum load the build process is allowed to cause with the -l flag, please review the documentation of GNU make.

Compiler and linker options

The following compiler and linker options in the makefile.include should be reviewed and eventually modified before starting the build process:

• CXX: This should be a C++17-compatible C++ compiler with MPI support.
• CXXFLAGS: Specifies the flags for the C++ compiler.
• INCLUDE: Paths in which to look for headers of required libraries. Here the include directory of BLAS should be listed.
• FC (deprecated)
• FFLAGS (deprecated)

Compile-time options

• -DVASPML_DEBUG_LEVEL: If set to 1, 2 or 3 enables various sanity checks during runtime with low, medium and high impact on performance, respectively.
• -DVASPML_USE_CBLAS: Use CBLAS (C interface for BLAS routines) for linear algebra. This is the default and should always be used.
• -DVASPML_USE_MKL: Use Intel MKL for linear algebra.
• -DVASPML_FORTRAN_MATH (deprecated): Enable legacy Fortran math routines.

Makefile options

• --no-color: Disables colored output of makefiles.
• --no-logo: Disables the logo VASPml logo output.

Automatic patching and compilations of LAMMPS

make lammps -j

Technical details

From a technical standpoint LAMMPS and VASPml interact in the following way: on the LAMMPS side a new class PairVASP (inheriting from Pair) is implemented in pair_vasp.cpp/h. Its purpose is to transfer the neighbor lists to VASPml, trigger processing, and receive back the energy and force contributions. VASPml enters the received neighbor list data into its own structures and computes energy and force predictions according to the pre-trained machine-learned force field. A typical build for the combination of the two codes requires to first compile the libvaspml library. Then, LAMMPS is patched with the additional pair_vasp.cpp/h files, which are automatically compiled during the LAMMPS build. In the final stage, LAMMPS is linked to the libvaspml library, resulting in a patched executable. This can be done manually but VASPml also offers a convenient automated way covering all steps (make lammps).