Not so Wheely great news.
Installation ^new^ | Vasp 5.4.4
From the root directory ( vasp.5.4.4 ), run the make command. This will compile the standard, gamma-only, and non-collinear versions automatically.
You can compile VASP using either the Intel toolchain (recommended for optimal performance on Intel hardware) or the GNU toolchain (open-source alternative).
Add to ~/.bashrc for convenience.
If you are using the newer Intel OneAPI , you may need to update the compiler commands from ifort to ifx (though ifort still works in most 2024/2025 environments). 5. The Compilation Process vasp 5.4.4 installation
: Copy arch/makefile.include.linux_intel_cuda and set your CUDA_ROOT path. Troubleshooting Common Errors
Before installing, ensure your Linux environment has the following installed:
Upon successful completion, the compiled binaries will be generated inside the bin/ directory ( bin/vasp_std , bin/vasp_gam , bin/vasp_ncl ). 6. Post-Installation Steps From the root directory ( vasp
To speed up the compilation process on multi-core systems, use the parallel make flag (e.g., make -j4 all ).
VASP 5.4.4 simplifies compilation by utilizing a centralized architecture. You must select a template file from the arch/ directory and copy it to the root directory as makefile.include . 1. Selecting the Template
Or, with an example SLURM submission script: Add to ~/
VASP 5.4.4 uses a makefile.include file to determine compiler flags and library paths. Do not modify the Makefile itself. Instead, copy a template from arch to the root directory.
This usually means your INCLUDE path in the makefile isn't pointing to the MKL include folder. Double-check your MKLROOT .
Navigate to the arch directory to find the makefile templates. Copy the template that best matches your architecture to the root directory.
3 Feb 2026 — Using prebuilt VASP. To load prebuilt VASP on Fir and Nibi, please do the following: For vasp/5.4.4 module load StdEnv/2023 intel/ Digital Research Alliance of Canada Build your own VASP 5 - Rosen Center for Advanced Computing
Run on 4 cores: