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line-profiler - https://pypi.org/project/line-profiler/

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Requirements

python  3.10:   module load itm-python/3.10 

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gprof2dot: pip install gprof2dot 4.

How to run?

1.  prepare a standard launch 
2. Copy python  folder from /gss_efgw_work/work/g2fjc/jintrac/v220922/python  to some location on pfs for example: /pfs/work/g2pbloch/python 
3. Change JINTRAC_PYTHON_DIR  in rjettov (430 line) to python folder on pfs from step 2
4. Change run_python_driver (line 49) in /pfs/work/g2pbloch/python :
5. cProfile :  mpirun --allow-run-as-root -np $NPROC python -u  -m cProfile -o jintrac.prof /pfs/work/g2pbloch/jetto_profiler/jintrac_imas_driver.py  mpi 
6. line-profiler : mpirun --allow-run-as-root -np $NPROC python -u  -m kernprof -l /pfs/work/g2pbloch/jetto_profiler/jintrac_imas_driver.py  mpi 

7. When we use line-profiler we must add wrapper to profiling function. In this case we should add @profile  upper jintrac_imas_driver function in jintrac_imas_driver.py  : 

   Code Block
   language py title function wrapper
   @profile def jintrac_imas_driver(params, components, mpi='no'): """JINTRAC-IMAS generic workflow driver."""

   
   

8. Run ./rjettov -S -I -p -x64 test v220922 g2fjc 

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cProfile analysis

To read data from test.prof we need python script. We can use e.g.

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Line-profiler analysis

To read data from jintrac_imas_driver.py.lprof  run: python -m line_profiler jintrac_imas_driver.py.lprof . These are the first few lines of the results :

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Line #      Hits         Time  Per Hit   % Time  Line Contents
   895         1   62545203.7 62545203.7     26.9      alenv = ALEnv(user_temp=user_tmp)
   917        22   49496025.7 2249819.4     21.3                  ids_bundle_input[ids_struct] = eval('DBentry.idsin.get("'+ids_struct+'")')
   922         1   83745046.9 83745046.9     36.0      tmpdict = bundle_copy(ids_bundle_input)
   956         2    4665617.1 2332808.6      2.0                          ids_bundle_input[elem] = DBentry.idsin.get_slice(elem, tstart, 3)
   966         1    6353190.5 6353190.5      2.7      ids_bundle_work = bundle_copy(ids_bundle_input)
   967         1    7884627.8 7884627.8      3.4      ids_bundle_updated = bundle_copy(ids_bundle_input)
  1022         3   14539266.0 4846422.0      6.2          ids_bundle_prev[item] = bundle_copy(ids_bundle_work,imas_control.get_ids_sublist_updates(item))

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Candidates for bottlenecks

From cProfile we can see, that 85% execution time jintrac_imas_driver.py spend on imas functions. Function ual_open_pulse  was called only 3 times. It execution time is 27s. Functions ual_read_data_array  and ual_read_data_scalar was called more than 2 milions times. 

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