Edit makefile.include to contain:
# Ubuntu/Debian sudo apt update sudo apt install build-essential gfortran cmake git wget sudo yum groupinstall "Development Tools" sudo yum install gcc-gfortran cmake wget vasp 5.4.4 installation
# Precompiler options CPP_OPTIONS = -DHOST=\"LinuxIFC\" \ -DMPI -Duse_collective -DMPI_BLOCK=8000 \ -DscaLAPACK -DCACHE_SIZE=4000 \ -Davoidalloc -Duse_bse_te \ -Dtbdyn -Dfock_dblbuf FC = mpiifort FCL = mpiifort CC = mpiicc CXX = mpiicpc Flags for optimization FFLAGS = -O2 -assume byterecl -xHost -heap-arrays 64 OFLAG = -O2 OFLAG_IN = $(OFLAG) DEBUG = -O0 -g -traceback Linking FCLFLAGS = -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -liomp5 -lpthread -lm -lstdc++ BLAS/LAPACK/FFTW via MKL LLIBS = -mkl=parallel No need for separate FFTW if using MKL Edit makefile
sudo apt install libopenblas-dev libfftw3-dev libscalapack-openmpi-dev Then set makefile.include : Use with MPI processes to reduce memory bandwidth contention
FFLAGS = -O2 -ffree-line-length-none -fopenmp -fallow-argument-mismatch OFLAG = -O2 DEBUG = -O0 -g -fbounds-check
With a working VASP 5.4.4 installation, you are now ready to compute accurate electronic structures, phonon spectra, and reaction barriers – pushing the frontiers of computational chemistry and condensed matter physics.
help([[ VASP 5.4.4 compiled with Intel oneAPI 2023.0 ]]) local version = "5.4.4" local base = "/opt/vasp/5.4.4" prepend_path("PATH", pathJoin(base, "bin")) setenv("VASP_HOME", base) For those who need peak performance, consider these tweaks: 7.1 Profile-Guided Optimization (PGO) Compile once with profiling flags ( -prof-gen for Intel), run a short benchmark, then recompile with -prof-use . This can yield 5-10% speedups. 7.2 Cache Size Tuning Adjust -DCACHE_SIZE based on your CPU's L3 cache (in KB). For a typical Xeon with 30MB L3, use -DCACHE_SIZE=30000 . 7.3 Hybrid MPI+OpenMP Add -D_OPENMP and -qopenmp to FFLAGS, set OMP_NUM_THREADS=2 or 4 . Use with MPI processes to reduce memory bandwidth contention. 7.4 Linking Against CUDA-Aware MPI (for GPU builds) Add -DMPI_BLOCK=131072 for better GPU-MPI performance. Use NCCL (NVIDIA Collective Communications Library) by adding -DUSENCCL . Conclusion Installing VASP 5.4.4 is a rite of passage for computational materials scientists. While the process involves many moving parts – compilers, MPI, libraries, and architecture-specific flags – the result is a powerful simulation engine that can tackle problems ranging from catalytic surfaces to battery materials.