At the Tartu HPC cluster I have a limit for number of files, which prevents me from having too many conda environments. So, after I have ruined my base environment, I decided to finally switch to Singularity\/Apptainer. Here is a simple recipe for creating an apptainer which is equivalent to standard conda installation. It is just an example. Note that AMD\/Intel optimized apptainers will run 10\u201320% faster than the conda one.<\/p>\n\n\n\n
P.S. I have ruined my base environment while trying to install XMGRACE, which is so much easier to use than writing a python code just to check calculations results.<\/p>\n\n\n\n
Bootstrap: docker\nFrom: continuumio\/miniconda3\n\n%post\n # Install necessary packages including InfiniBand support using apt\n apt-get update && \\\n apt-get install -y infiniband-diags perftest ibverbs-providers libibumad3 libibverbs1 libnl-3-200 libnl-route-3-200 librdmacm1 lldpad libdapl2 libdapl-dev rdmacm-utils ibverbs-utils && \\\n apt-get install -y grace povray && \\\n rm -rf \/var\/lib\/apt\/lists\/*\n\n # Configure conda\n conda install --solver=classic conda-forge::conda-libmamba-solver conda-forge::libmamba conda-forge::libmambapy conda-forge::libarchive\n conda install -y python=3.11\n\n # Install openmpi and ucx from conda\n conda install -y -c conda-forge openmpi=4.1.6=*hc5af2df* ucx\n\n # Install gpaw from conda\n conda install -y -c conda-forge gpaw=24*=*openmpi*\n\n # Install other packages\n conda install -y -c conda-forge dftd4 dftd4-python\n\n # Optionally, clean up Conda to reduce the image size\n conda clean --all -f -y\n\n%environment\n # Activate the base environment\n source \/opt\/conda\/etc\/profile.d\/conda.sh\n conda activate base<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"At the Tartu HPC cluster I have a limit for number of files, which prevents me from having too many conda environments. So, after I have ruined my base environment, I decided to finally switch to Singularity\/Apptainer. Here is a simple recipe for creating an apptainer which is equivalent to standard conda installation. It is… Read More<\/a><\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12],"tags":[53],"class_list":["post-903","post","type-post","status-publish","format-standard","hentry","category-know-how","tag-gpaw"],"_links":{"self":[{"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/posts\/903","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/comments?post=903"}],"version-history":[{"count":4,"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/posts\/903\/revisions"}],"predecessor-version":[{"id":907,"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/posts\/903\/revisions\/907"}],"wp:attachment":[{"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/media?parent=903"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/categories?post=903"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/doublelayer.eu\/vilab\/wp-json\/wp\/v2\/tags?post=903"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}