Vasp 5.4.4 Installation

Installing VASP 5.4.4 (The Vienna Ab initio Simulation Package) is a milestone for many computational researchers. While newer versions exist, 5.4.4 remains a "workhorse" version due to its stability and compatibility with various legacy scripts.

Because VASP is not a "plug-and-play" application, you must compile it from source code specifically for your hardware. This guide covers the standard installation process using Intel Compilers and MKL, which generally yields the best performance. 1. Prerequisites and Dependencies

Before you begin, ensure your system has the necessary build environment. You will need:

VASP Source Code: A licensed copy (typically vasp.5.4.4.tar.gz).

Fortran & C Compilers: Intel ifort and icc are highly recommended.

Numerical Libraries: Intel MKL (Math Kernel Library) for FFTW, BLAS, and LAPACK. MPI Library: Intel MPI or OpenMPI for parallel execution. 2. Preparing the Source Code

First, create a directory for the installation and unpack your source file:

mkdir -p ~/software/vasp cd ~/software/vasp tar -zxvf vasp.5.4.4.tar.gz cd vasp.5.4.4 Use code with caution. 3. Configuring the Makefile

VASP 5.4.4 uses a modular makefile system. Instead of a complex configuration script, you choose a template from the arch directory that matches your setup. Look at the templates: ls arch.

Copy the most common Intel/Linux template to the root folder: cp arch/makefile.include.linux_intel ./makefile.include Use code with caution. 4. Editing makefile.include

Open the makefile.include file with a text editor (like nano or vi). For a standard Intel Parallel Studio / OneAPI setup, you usually need to verify these paths:

MKLROOT: Ensure this points to your Intel MKL installation directory. vasp 5.4.4 installation

OBJECTS: For version 5.4.4, ensure the FFTW wrappers are correctly linked.

BLACS/SCALAPACK: If you are running on a cluster, verify that the ScaLAPACK lines are uncommented to enable parallel linear algebra.

Pro-Tip: 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 can be built in three different versions. It is best to build all of them: std: The standard complex version (for most calculations).

gam: The Gamma-point only version (faster for large cells with only one k-point). ncl: The non-collinear version (for spin-orbit coupling). Run the following command to build all three: make all Use code with caution.

Note: This process can take 10 to 30 minutes depending on your CPU speed. 6. Verifying the Executables

Once the compilation finishes, a bin directory will be created inside the vasp.5.4.4 folder. You should see: vasp_std vasp_gam vasp_ncl

Add this directory to your .bashrc or .zshrc so you can call VASP from anywhere: export PATH=$PATH:~/software/vasp/vasp.5.4.4/bin Use code with caution. 7. Common Troubleshooting

"Error: mkl_fftw.h not found": This usually means your INCLUDE path in the makefile isn't pointing to the MKL include folder. Double-check your MKLROOT.

Segmentation Faults: Often caused by a stack size limit. Use ulimit -s unlimited in your submission script before running the VASP command.

Rank Errors: Ensure the version of MPI used to compile VASP is the same one used to run it (mpirun vs mpiexec). Installing VASP 5

I'll assume you want installation instructions and a feature-preparation checklist for VASP 5.4.4 (Vienna Ab initio Simulation Package). I'll provide (1) concise build/install steps for a typical Linux cluster (dependencies, compile options, example Makefile targets), and (2) a short "prepare a feature" checklist for developing/adding a feature in the VASP source (coding, testing, compilation, validation). If this assumption is wrong, tell me what OS/cluster and compiler/MPI/BLAS/LAPACK you use.

3. Memory optimization

For large systems (>100 atoms), add to INCAR:

NPAR = 4          # Number of bands groups (tune)
LPLANE = .TRUE.   # Planar FFT decomposition

3. Preprocessor Options

Check the CPP_OPTIONS line. Standard options include:

CPP_OPTIONS = -DHOST=\"LinuxIFC\" -DMPI -DMPI_BLOCK=8000 -Duse_collective \
              -DscaLAPACK -DCACHE_SIZE=4000 -Davoidalloc -DNGZhalf \
              -Duse_shmem

VASP 5.4.4 — Installation report (comprehensive, practical)

Summary

• VASP 5.4.4 is a legacy (5.x) release of the Vienna Ab‑initio Simulation Package; it requires a paid license and is distributed to licensees from the VASP project. Building is done from source on Linux and typically requires Fortran/C compilers, MPI, BLAS/LAPACK/ScaLAPACK, FFTW (or MKL FFT), and optional CUDA/MAGMA for GPU support. Below is a structured, actionable guide covering prerequisites, preparatory steps, makefile tuning, common build recipes (Intel/MKL, GNU+FFTW, GPU), testing, common pitfalls and suggested verification.

Prerequisites and licensing

• Obtain the VASP 5.4.4 source tarball from the VASP maintainers (license required).
• Supported tooling (typical): Fortran compiler (ifort/mpiifort, pgfortran, gfortran), C/C++ compilers (icc/icc/ icpc or gcc/g++), MPI implementation (Intel MPI, OpenMPI, MVAPICH2), numerical libraries: BLAS/LAPACK (or MKL), ScaLAPACK & BLACS (for parallel large-scale jobs), FFT library (FFTW3 or MKL FFTW interface), optional: CUDA toolkit + MAGMA for GPU port.
• OS: x86_64 Linux (RHEL/CentOS/Ubuntu variants commonly used). Kernel/libc compatibility matters if using prebuilt MKL/Intel toolkits.

Directory structure (VASP 5.x)

• Root directory layout:
  • arch/: sample makefile.include.arch files
  • src/: source files and .objects lists
  • build/: build subdirectories for vasp_std, vasp_gam, vasp_ncl, etc.
  • bin/: destination for executables
• Copy a suitable arch/makefile.include.* to root/makefile.include and edit to match your environment.

High‑level steps

1. Unpack source:
   • tar -xzf vasp.5.4.4.tar.gz
   • cd vasp.5.4.4
2. Choose and copy architecture template:
   • cp arch/makefile.include.linux_intel ./makefile.include (or linux_gfortran, linux_intel_cuda, etc.)
3. Edit makefile.include to point to compilers, libraries, flags (detailed below).
4. Build: make all (or make std gam ncl; or make all 2>&1 | tee vasp-make.log)
5. Test basic run with a small example (serial/parallel); set OMP_NUM_THREADS appropriately.

Key makefile.include parameters and options

• Compiler variables:
  • FC / FCL / FC_LIB — Fortran compiler (e.g., mpiifort, mpif90, mpifort, gfortran)
  • CC / CXX / CC_LIB — C/C++ compilers (icc/icpc or gcc/g++)
  • CXX_PARS — C++ compiler for parser library (icpc/g++)
• Preprocessor options:
  • CPP_OPTIONS: defines for HOST, MPI, compiler family, ILP64 vs LP64, GPU flags (-DCUDA_GPU), scaLAPACK usage (-DscaLAPACK), etc.
  • Choose ILP64 only if your BLAS/ScaLAPACK/MKL were built with ILP64 (indices 64-bit).
• Numerical libraries linking:
  • MKL usage (Intel): set MKLROOT, MKL_PATH = $(MKLROOT)/lib/intel64; BLAS/LAPACK/SCALAPACK/BLACS configured via MKL flags or static libs (libmkl_scalapack_lp64.a, -lmkl_intel_lp64, -lmkl_core, -lmkl_sequential or -lmkl_intel_thread + libiomp5).
  • FFTW usage: either point OBJECTS to include MKL FFTW interface libfftw3xf_intel.a or link against FFTW3 (fftw3 or fftw3f) libraries (FFTW3_MPI for parallel).
  • LLIBS holds SCALAPACK, LAPACK, BLAS and FFTW libs e.g. LLIBS = $(SCALAPACK) $(FFTW3_LIBS_MPI) $(LAPACK) $(BLAS)
• Objects:
  • OBJECTS = fftmpiw.o fftmpi_map.o fft3dlib.o fftw3d.o [plus MKL fftw lib path if used]
  • For GPU builds, OBJECTS_GPU and GPU-specific flags (CPP_GPU) and FFTW GPU variants (fftw3d_gpu.o).
• Compiler flags:
  • FFLAGS, FFLAGS_LIB, CFLAGS, OFLAG, DEBUG — set optimization for your CPU (e.g., -O3 -xHOST or -xCORE-AVX2 for Intel; conservative flags for portability).
  • FREE = -free -names lowercase (for Intel) or -ffree-form for gfortran as needed.
• MPI and threading:
  • Typical VASP builds use MPI for parallelism and OMP_NUM_THREADS=1 at runtime; OpenMP support can be enabled but mixing MPI+OpenMP requires tuning.

Typical build recipes

1. Intel compilers + MKL (recommended for performance)

• Modules / environment:
  • source /opt/intel/oneapi/setvars.sh (or use module load intel/… impi mkl)
• Choose arch template: makefile.include.linux_intel
• Example important edits:
  • FC = mpiifort
  • FCL = mpiifort -mkl=sequential
  • CPP_OPTIONS include -DMKL_ILP64 only if MKL built ILP64
  • OBJECTS add: $(MKLROOT)/interfaces/fftw3xf/libfftw3xf_intel.a (or build libfftw3xf_intel.a per Intel note)
  • MKL linking: SCALAPACK = $(MKL_PATH)/libmkl_scalapack_lp64.a $(BLACS)
  • LLIBS = $(SCALAPACK) $(LAPACK) $(BLAS)
• Build:
  • make all
• Verify:
  • ldd bin/vasp_std should list libmkl_*.so and libmpifort / libmpi.

2. GNU compilers + FFTW + ScaLAPACK (open stack)

• environment:
  • module load gcc openmpi fftw scalapack
• Template: makefile.include.linux_gfortran (or adjust linux_intel)
• Key edits:
  • FC=mpif90 or mpifort (OpenMPI)
  • BLAS/LAPACK/SCALAPACK variables point to system-provided libs (or link to OpenBLAS)
  • INCS and OBJECTS: set FFTW3 include and library locations (FFTW3_LIBS_MPI)
  • LLIBS = $(SCALAPACK) $(FFTW3_LIBS_MPI) $(LAPACK) $(BLAS)
• Build:
  • make std (or make all)
• Note: performance often lower than MKL but portable.

3. GPU (CUDA) build with MAGMA

• Requirements: CUDA toolkit compatible with compute capability of GPUs, MAGMA built against MKL and matched compilers, patched VASP GPU sources (arch/makefile.include.linux_intel_cuda).
• Edits:
  • Enable CPP_GPU flags (-DCUDA_GPU etc), set CUDA_ROOT and NVCC, add CUDA_LIB to LLIBS.
  • Set MAGMA_ROOT path and add MAGMA libs to LLIBS.
  • OBJECTS_GPU includes fftw3d_gpu.o etc.
• Build:
  • make all (may build CPU and GPU targets separately)
• Runtime: assign GPUs per MPI rank correctly; mapping and affinity tuning required. Typical recommendation: 1 MPI rank per GPU or multiple ranks per GPU (bench test).

Patches and version notes

• VASP 5.4.4 has known patches posted on the VASP/wiki; some distributions include small patches (e.g., fixes for SCAN stress, Thomas‑Fermi potential, optB88 issues). Apply provided patch files in root directory with:
  • patch -p0 < patch.5.4.4*.gz (after gunzip) per instructions.
• The VASP wiki (Installing_VASP.5.X.X) is authoritative for 5.x build details and lists patch files.

Common build and runtime pitfalls (and fixes) VASP 5

• Wrong ILP64 vs LP64 setting: linking mismatches between BLAS/ScaLAPACK and compiled code cause symbol or runtime errors; ensure CPP_OPTIONS and MKL flags match how MKL/ScaLAPACK were built.
• FFTW vs MKL FFT mismatch: If using MKL FFTW interface, OBJECTS or linked archive must include libfftw3xf_intel.a or equivalent—otherwise missing symbol errors in FFT routines occur.
• MPI ABI mismatch: use compilers provided MPI wrappers (mpiifort/mpif90) and ensure the MPI used at compile-time equals runtime MPI.
• Undefined symbols at link: ensure LLIBS order and full paths to static libs as needed (ScaLAPACK before LAPACK/BLAS).
• For GPU runs: CUDA driver vs toolkit mismatch gives errors like “CUDA-capable devices busy/unavailable” or pinned memory registration failures; verify driver and CUDA runtime compatibility and correct GPU affinity.
• OpenMP and MPI thread oversubscription: set OMP_NUM_THREADS=1 unless expressly tuning hybrid runs.

Testing and verification

• Basic test: run a tiny example serial or few‑rank parallel job with known INCAR/POSCAR/POTCAR and check OUTCAR/OSZICAR for normal convergence.
• Check linked libraries:
  • ldd bin/vasp_std | grep -E 'mkl|fftw|mpi|mpifort'
• Run a short SCF and compare energy to known reference for simple systems (e.g., bulk Si) to validate functional/precision behavior.
• For parallel correctness: run with different MPI sizes and verify identical energies within numerical noise.

Performance tips

• Use vendor-optimized BLAS/LAPACK (Intel MKL) for best CPU performance.
• Compile with CPU-specific optimization flags (-xHOST or -march=native) but prefer portable builds for mixed-node clusters.
• For hybrid GPU runs, benchmark different MPI ranks per GPU and OMP thread counts; typical best performance varies by workload.
• Use proper CPU‑GPU affinity and ensure MPI rank ↔ GPU mapping is consistent (some VASP GPU patches improve mapping performance).

Example minimal Intel+MKL build snippet (illustrative)

• In makefile.include:
  • FC = mpiifort
  • FCL = mpiifort -mkl=sequential
  • CPP_OPTIONS = -DHOST="LinuxIFC" -DMPI -DIFC -DMKL_ILP64 -DscaLAPACK ...
  • MKL_PATH = $(MKLROOT)/lib/intel64
  • OBJECTS = fftmpiw.o fftmpi_map.o fft3dlib.o fftw3d.o $(MKLROOT)/interfaces/fftw3xf/libfftw3xf_intel.a
  • SCALAPACK = $(MKL_PATH)/libmkl_scalapack_lp64.a -lmkl_blacs_intelmpi_lp64
  • LLIBS = $(SCALAPACK) $(LAPACK) $(BLAS)
• Build:
  • source /opt/intel/oneapi/setvars.sh
  • make all 2>&1 | tee vasp-make.log

Maintenance and reproducibility

• Record compiler versions, MKL/FFT/MPI versions, kernel/OS, and exact makefile.include used (place copy in build logs).
• Save vasp_std binary and run ldd output for later reproducibility and debugging.
• Keep small verification inputs and outputs as regression tests when recompiling.

Useful references (official/community)

• VASP Wiki — Installing_VASP.5.X.X (detailed makefile.include guidance, objects lists, patches).
• Intel application notes — building VASP with Intel compilers/MKL (useful for MKL FFTW interface and libfftw3xf).
• HPC center pages (e.g., OSC) describing local module-based builds and MPI variants.

If you want, I can:

• Produce a ready-to-run makefile.include tuned to a specific environment (specify OS/distribution, compiler versions, MPI, MKL vs FFTW, GPU/no‑GPU).

VASP 5.4.4 is a widely used version of the Vienna Ab initio Simulation Package, valued for its stability and features like the SCAN functional. While newer versions exist, many researchers stick with 5.4.4 for consistency in ongoing projects. 🛠 Prerequisites and Dependencies

Before beginning, ensure your system has the mandatory software:

Fortran and C Compilers: Intel Fortran (ifort) or GNU Fortran (gfortran).

MPI Implementation: Required for parallel versions (e.g., Intel MPI or OpenMPI). Numerical Libraries: BLAS & LAPACK: Basic linear algebra. ScaLAPACK: Required for parallel execution. FFTW: Handles Fast Fourier Transforms.

Intel MKL: Highly recommended for performance on Intel-based systems. 🏗 Installation Steps

The build system for VASP 5.4.4 relies on a high-level makefile and specific architecture files. 1. Extract the Source Code Knowledge Base: Anvil User Guide: Installing applications

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Part 1: Prerequisites – What You Need Before You Start

Before typing a single make command, you must ensure your system meets the requirements. VASP 5.4.4 is designed for Linux/Unix systems (including macOS with modifications, but this guide focuses on Linux HPC clusters).