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offline_correlator: a light-weight correlator for the MWA. Takes VCS data files and correlates as per the parameters of the linked xGPU library
usage: offline_correlator -c <coarse_channel> -d <infile> [options]
Options:
   -e EDGES
        Set EDGES channels at both top and bottom of the band to 0 [default: 0]
   -h
        Display this help and exit
   -n CHAN_AVERAGE
        Average CHAN_AVERAGE adjacent channels in the final output [default: 4]
   -o OBSID
        The observation ID of the input VCS data [required]
   -r DUMPS_PER_SECOND
        The number of correlator dumps per second to write to file [default: 1]
   -s STARTTIME
        The time (in Unix seconds) corresponding to the input file[required]

#!/bin/bash -l

#SBATCH --nodes=1
#SBATCH --mem=370gb
#SBATCH --partition=gpuq
#SBATCH --gres=gpu:1
#SBATCH --time=00:10:00
#SBATCH --account=mwavcs
#SBATCH --export=NONE

module use /pawsey/mwa/software/python3/modulefiles
module load vcsbeam/correlator

INPUT_DATA_FILE=/path/to/recombined/data/file/1313388760_1313388762_ch144.dat
START_SECOND=1313388762
DUMPS_PER_SECOND=20 # This sets the output time resolution
                    # (e.g. 20 --> 1/20 = 0.05s = 50 ms)
                    # Minimum allowed resolution is 2 ms
CHANS_TO_AVERAGE=4 # This sets the output frequency resolution
                   # (e.g. 4 --> 4x10 kHz = 40 kHz)
GPUBOX_CHANNEL_NUMBER=20 # This should be chosen to "match" the input channel
                         # This is not easy! (mwalib handles this, but at the
                         # moment, offline_correlator is not using mwalib)
OUTPUT_PREFIX=1313388760 # Output files begin with this

srun -N 1 -n 1 offline_correlator \
    -d ${INPUT_DATA_FILE} \
    -s ${START_SECOND} \
    -r ${DUMPS_PER_SECOND} \
    -n ${CHANS_TO_AVERAGE} \
    -c ${GPUBOX_CHANNEL_NUMBER} \
    -o ${OUTPUT_PREFIX}