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===== Python to C =====

When installing https://mtazzari.github.io/galario/ via miniconda3 the the web site states "Due to technical limitations, the conda package does not support GPUs at the moment. If you want to use a GPU, you have to build galario by hand."

A compilation by hand yields two standalone libraries and presumably GPU functionality. There is an example of an invocation using ''-llibgalario_cuda''.

But we have python code so my thought was to pass these two standalone libraries via environment variable to the compiler.

https://nuitka.net/ source was downloaded and used directly.

<code>

  cd /usr/local/src/tmp/
  tar zxvf /zfshomes/hmeij/amhughes/Nuitka-0.6.16.1.tar.gz
  cd Nuitka-0.6.16.1/
  ln -s /zfshomes/hmeij/amhughes/galario_SS-6.py

#  make sure  pip installe cpython in the python of choice
#  miniconda3's python 3.8 (source the code initialization block)

# be sure to get a recent gcc compiler

  export PATH=/share/apps/CENTOS6/gcc/9.2.0/bin:$PATH
  export LD_LIBRARY_PATH=/share/apps/CENTOS6/gcc/9.2.0/lib64:$LD_LIBRARY_PATH
  export LD_LIBRARY_PATH=/share/apps/CENTOS6/gcc/9.2.0/lib:$LD_LIBRARY_PATH

# then generate a centos 7 binary

  python  bin/nuitka --follow-imports galario_SS-7.py

</code>

That all worked and a sample job scheduler is listed below.  It is claimed that the C binary will run 300% faster than the python code.  We'll see what the users say.

Now to try to pass the standalone libraries I tried this ...

<code>

# cuda 9.2
export CUDAHOME=/usr/local/n37-cuda-9.2
export PATH=/usr/local/n37-cuda-9.2/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/n37-cuda-9.2/lib64:$LD_LIBRARY_PATH
which nvcc

# fftw3
export FFTW_HOME=/share/apps/CENTOS7/fftw/3.3.8
export PATH=/share/apps/CENTOS7/fftw/3.3.8/bin:$PATH
export LD_LIBRARY_PATH=$FFTW_HOME/lib:$LD_LIBRARY_PATH

# for gpu we have a c++ galario libraries
export LD_LIBRARY_PATH=/share/apps/CENTOS7/galario/1.2.2/usr/local/lib:$LD_LIBRARY_PATH

# attempt at linking those libraries
CPATH=/share/apps/CENTOS7/galario/1.2.2/usr/local/include \
LIBRARY_PATH=/share/apps/CENTOS7/galario/1.2.2/usr/local/lib    \
python  bin/nuitka --follow-imports galario_SS-7gpu.py

</code>

It compiled but when invoked it does not find any cuda routines. That may be because I can not find any cuda python code in the git repository either.

=== sample job ===

<code>

#!/bin/bash
rm -f err-mpi-7c out-mpi-7c

# need conda initialization code block in ~/.bashrc, or next lines

# queues mwgpu, amber128 and exx96
#BSUB -q exx96
#BSUB -o out-mpi-7c
#BSUB -e err-mpi-7c
#BSUB -J test
#BSUB -R "span[hosts=1]"
#BSUB -n 8

# miniconda3
source /share/apps/CENTOS7/amber/miniconda3/etc/profile.d/conda.sh
export PATH=/share/apps/CENTOS7/amber/miniconda3/bin:$PATH
export LD_LIBRARY_PATH=/share/apps/CENTOS7/amber/miniconda3/lib:$LD_LIBRARY_PATH
which mpirun python conda

# wrapper handles  mpirun invocation
openmpi-mpirun \
./galario_SS-7.bin 'Sz_46.txt' \
1.28e-3 36.7 0.339 -1.0 1.0 10.9 61.7 0.46 -0.47 5 12 \
--outdir "output"
~

</code>



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