Python software on Archer: Difference between revisions

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module load pc-numpy
module load pc-numpy
module load pc-scipy
module load pc-scipy
2) Enter virtual environment containing all additional modules (AFTER loading python and the central modules
2) Enter virtual environment containing all additional modules (AFTER loading python and the central modules)
source /work/e507/e507/ap837/code/venv_pyscf/bin/activate
source /work/e507/e507/ap837/code/venv_pyscf/bin/activate
3) If code uses intel libraries: (errors like:
3) If code uses intel libraries: (errors like:

Revision as of 15:43, 30 August 2017

For running Python on work nodes on Archer, there are python-compute (native) and anaconda-compute modules available. Users are discouraged from using anaconda-compute because it is not optimised for running on Archer. There are some preinstalled packages for python-compute and they begin with pc-. For installation of additional packages, virtual environments are encouraged.

For more info see: http://www.archer.ac.uk/documentation/user-guide/python.php

When compiling Python software (like PySCF) Archer by default builds all libraries as static libraries. This leads to errors like:

 ImportError Cannot import name ...

or

 File "/work/y07/y07/cse/numpy/1.9.2-libsci/lib/python2.7/site-packages/numpy/ctypeslib.py", line 128, in load_library
   raise OSError("no file with expected extension")
 OSError: no file with expected extension

and other errors.

To prevent dynamic libraries from becoming static you must:

 export CRAYPE_LINK_TYPE=dynamic

before the compilation. For more information see: http://www.archer.ac.uk/documentation/user-guide/development.php#sec-4.6

In submission script itself, do not forget to:

1) Load python and all modules supplied centrally

 module load python-compute
 module load pc-numpy
 module load pc-scipy

2) Enter virtual environment containing all additional modules (AFTER loading python and the central modules)

 source /work/e507/e507/ap837/code/venv_pyscf/bin/activate

3) If code uses intel libraries: (errors like:

 OSError: libmkl_intel_lp64.so: cannot open shared object file: No such file or directory
 OSError: libiomp5.so: cannot open shared object file: No such file or directory

) do:

 source /opt/intel/bin/compilervars.sh intel64

4) When using numpy, the following error may occur:

 Intel MKL FATAL ERROR: Cannot load libmkl_avx.so or libmkl_def.so

Tha solution is to do:

 export LD_PRELOAD=/opt/intel/mkl/lib/intel64/libmkl_core.so:/opt/intel/mkl/lib/intel64/libmkl_sequential.so

as found here http://debugjournal.tumblr.com/post/98401758462/intel-mkl-dynamic-link-library-error.

5) For PySCF, since we are using old numpy, you need to comment out warning in __init__.py in the pyscf folder

 #if LooseVersion(numpy.__version__) <= LooseVersion('1.8.0'):
 #    raise SystemError("You're using an old version of Numpy (%s). "
 #                      "It is recommended to upgrad numpy to 1.8.0 or newer. \n"
 #                      "You still can use all features of PySCF with the old numpy by removing this warning msg. "
 #                      "Some modules (DFT, CC, MRPT) might be affected because of the bug in old numpy." %
 #                      numpy.__version__)