jtchilders/singularity_mpi_test_recipe:intelpython

$ singularity pull shub://jtchilders/singularity_mpi_test_recipe:intelpython

Singularity Recipe

Bootstrap: docker
From: intelpython/intelpython3_full:latest

%setup
   # make directory for MPICH
   mkdir ${SINGULARITY_ROOTFS}/mpich
   cd ${SINGULARITY_ROOTFS}/mpich/
   wget -q http://www.mpich.org/static/downloads/3.2.1/mpich-3.2.1.tar.gz
   tar xf mpich-3.2.1.tar.gz --strip-components=1
   
   # check out singularity
   cd ${SINGULARITY_ROOTFS}
   git clone https://github.com/uber/horovod.git
   cd horovod
   git checkout v0.14.1

%post
   # install development tools
   # yum update -y
   # yum groupinstall -y "Development Tools"
   # yum install -y gcc
   # yum install -y gcc-c++
   apt-get update
   apt-get install build-essential --assume-yes
   apt-get install gcc g++ gfortran --assume-yes

   
   # install MPICH
   cd /mpich
   # disable the addition of the RPATH to compiled executables
   # this allows us to override the MPI libraries to use those
   # found via LD_LIBRARY_PATH
   ./configure --prefix=/mpich/install --disable-wrapper-rpath
   make -j 4 install
   # add to local environment to build pi.c
   export PATH=$PATH:/mpich/install/bin
   export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/mpich/install/lib
   
   export PATH=/opt/conda/bin:$PATH
   export PYTHONPATH=/opt/conda/lib/python3.6/site-packages
   cd /horovod
   HOROVOD_WITHOUT_PYTORCH=1 HOROVOD_WITH_TENSORFLOW=1 python setup.py build
   HOROVOD_WITHOUT_PYTORCH=1 HOROVOD_WITH_TENSORFLOW=1 python setup.py install --prefix=/opt/conda 

   # install keras
   export PATH=/opt/conda/bin:$PATH
   conda install -y keras

Collection


View on Datalad

Metrics

key value
id /containers/jtchilders-singularity_mpi_test_recipe-intelpython
collection name jtchilders/singularity_mpi_test_recipe
branch master
tag intelpython
commit af2299bc9c2e9c8fc2519ab52e92588b1761745d
version (container hash) 45e3fdd3fe3f71d28c27850ae25a30e9
build date 2018-10-02T17:54:24.223Z
size (MB) 4064
size (bytes) 1206132767
SIF Download URL (please use pull with shub://)
Datalad URL View on Datalad
Singularity Recipe Singularity Recipe on Datalad
We cannot guarantee that all containers will still exist on GitHub.