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Environment
To obtain the environment to run psana2, execute the following:
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source /reg/g/psdm/sw/conda2/manage/bin/psconda.sh |
Note that psana2 LCLS-II psana is not compatible with psana1LCLS-I psana, so environments must activate one or the other, but not both.
Example Script
If you have xtc files (with associated smd files) you can run this script with MPI: PS_SRV_NODES=2; mpirun -n 6 python example.py
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from psana import DataSource import numpy as np # called back on each SRV node, for every smd.event() call below def test_callback(data_dict): print(data_dict) ds = DataSource(exp='xpptut13', run=1, dir='.tmp') # batch_size here specifies how often the dictionary of information # is sent to the SRV nodes smd = ds.smalldata(filename='my.h5', batch_size=5, callbacks=[test_callback]) run = next(ds.runs()) # necessary (instead of "None") since some ranks may not receive events # and the smd.sum() below could fail arrsum = np.zeros((2), dtype=np.int) for i,evt in enumerate(run.events()): myones = np.ones_like(arrsum) smd.event(evt, myfloat=2.0, arrint=myones) arrsum += myones if smd.summary: smd.sum(arrsum) smd.save_summary({'summary_array' : arrsum}, summary_int=1) smd.done() |
MPI Task Structure
To allow for scaling, many hdf5 files are written, one per "SRV" node. The total number of SRV nodes is defined by the environment variable PS_SRV_NODES (defaults to 0). These many hdf5 files are joined by psana into what appears to be one file using the hdf5 "virtual dataset" feature.
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