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psana can scale to allow for high rate analysis.  For example, many hdf5 files of small user-defined data (described above in Example Script Producing Small HDF5 File) can be written, one per "SRV" node in the diagram below.  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.  Similarly, multiple nodes can be used for filtering ("EB" nodes in the diagram below) and multiple nodes can be used to process big data in the main psana event loop ("BD" nodes in the digram below).  The one piece that cannot be scaled (currently) to multiple nodes is the SMD0 (SMallData) task, which reads the timestamps and fseek offsets from each tiny .smd.xtc2 file produced by the DAQ (typically one per detector, or one per detector segment, although it can contain more than one segment or detector).  This task joins together the relevant data for each shot ("event build") using the timestamp.  This SMD0 task is multi-threaded, with one thread for each detector.  For highest performance it is important that all SMD0 threads be allocated an entire MPI node.

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Running a large job

Below shows how to setup a slurm job script to run a large job. This script uses setup_hosts_openmpi.sh  (also provided below) to assign a single node to SMD0 (see diagram above) and distribute all other tasks (EB, BD, & SRV) to the rest of available nodes. After source setup_hosts_openmpi.sh , you can use $PS_N_RANKS and $PS_HOST_FILE in your mpirun command. 

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