#Vasp 5.4.4 patch mac os#
This time I started with a clean install of Mac OS 10.11 (El Capitan).
#Vasp 5.4.4 patch update#
I will update with more codes and tools as I find time, and always happy to receive suggestions.Įvery few years, I give my laptop a fresh start and remove all the debris (applications, libraries, updates) that have built up. It now installs, including the gui, in one command: The atomistic simulation environment is a useful set of Python tools and modules. src/lib/getshmem.c add #define SHM_NORESERVE 010000 to the end of the include statements.ĭistrk: each k-point on 4 cores, 1 groups There is one bug to fix before you type make: in. We will also remove DscaLAPACK from the pre-compiler options and set SCALAPACK =. The file needs to be modified to point to the correct compilers (I used icc, icpc, and mpifort).
I downloaded the latest version (5.4.4), which has streamlined the install process. I use a range of electronic structure packages, but VASP is the old reliable. If harmonic phonons are not enough for you, then Phono3py lets you calculate phonon-phonon interactions, but it gets very expensive to compute. % conda install numpy scipy h5py pyyaml matplotlib openblas
The installation used to be multi-step, but Conda makes life easier (adapted from Togo’s official guide): I use this open-source lattice-dynamics package a lot. bash_profile:Įxport DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:/usr/local/openmpi-2.1.1/lib/Įxport PATH=./:/usr/local/openmpi-2.1.1/bin:$PATH configure -prefix=/usr/local/openmpi-2.1.1 CC=icc FC=ifort F77=ifortīe patient… it can easily take 20 minutes.
#Vasp 5.4.4 patch code#
To enable parallelism, I downloaded the latest source code of openmpi (2.1.1). Source /opt/intel/bin/compilervars.sh intel64 Source /opt/intel/mkl/bin/mklvars.sh intel64 The package installs in a few clicks, but be sure source the variables in your. For non-commericial purposes Intel Composer is now free for OS X. It is possible to survive using gnu compilers and freely available maths libraries, but Intel Fortran and MKL tend to be faster and better tested (easier to compile). I am happy with the results so far, and the standard install gives a good base set of packages. Python package and environment maintenance can cause headaches, so this time I went with Conda for Mac. For video and image editing ffmpeg and imagemagick are essential. My base applications include: (standard office) Dropbox, Slack, MS Office ( Imperial link), Mactex, Texmaker, Mendeley (scientific computing) latest gcc/gfortran, iTerm, Textmate, XQuartz, Atom, Cyberduck, GitHub client (materials modelling) VESTA, Avogadro. Be sure to set up your bash_profile, ssh config, and vimrc files to make working faster and more comfortable. Open a Terminal and type make which triggers the system to install Xcode (if missing) and the command line tools module (basic UNIX commands including a gcc compiler). The first step is to install the command line tools.
I started with a clean install of Mac OS 10.12 (Sierra). It is not an absolute guide, but simply one way to get going. An update of previous entries for setting up an Apple computer for scientific computing.