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.. _nersc_cori:
=====================
cori.nersc.gov (XC40)
=====================
.. note::
These instructions are up-to-date as of July 2018.
GPAW
====
At NERSC it is recommened to install GPAW on Cori with Anaconda python. For
massivly parallel applications it is recommened to use `Shifter
<http://www.nersc.gov/research-and-development/user-defined-images/>`_.
GPAW can be built with a minimal ``customize.py``
.. literalinclude:: customize_nersc_cori.py
Load the GNU programming environment and set Cray environment for dynamic
linking::
export CRAYPE_LINK_TYPE=dynamic
module swap ${PE_ENV,,} PrgEnv-gnu
module load python
Create a conda environment for gpaw::
conda create --name gpaw python=3.6 pip numpy scipy matplotlib
Install ASE with pip while the Anaconda python module is loaded::
source activate gpaw
pip install ase
Build and install GPAW::
python setup.py build_ext
python setup.py install
To setup the environment::
module swap ${PE_ENV,,} PrgEnv-gnu
module load python
source activate gpaw
export OMP_NUM_THREADS=1
Then the test suite can be run from a batch script or interactive session with::
export MKL_CBWR="AVX"
srun -n 8 -c 2 --cpu_bind=cores gpaw-python -m gpaw test
.. note::
For all tests to pass enable MKL's conditional Numerical
Reproducibility mode with the `MKL_CBWR` environment variable.
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