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Digital Packaging Processor

Digital Packaging Processor. G. Hurford Conceptual Design Review - NJIT April 25, 2011. OVSA Expansion Software and Data Handling - Kickoff Meeting. 23-Oct-10. GH/JM+NJIT. OVSA-specific CASPER-based Miriad-based RHESSI-based. Monitor and Control. Operator. DSPU.

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Digital Packaging Processor

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  1. Digital Packaging Processor G. Hurford Conceptual Design Review - NJIT April 25, 2011

  2. OVSA Expansion Software and Data Handling - Kickoff Meeting 23-Oct-10 GH/JM+NJIT OVSA-specific CASPER-based Miriad-based RHESSI-based Monitor and Control Operator DSPU Antennas, receivers, analog subsystems NJIT Data Packaging Processor Interim Data Base Data selection, averaging, reformatting & calibration Burst identification Tohban Light curve, spectra display Archive Databases ~6 GB/day Light curve, spectra generation Map generation Map display Quick look & metadata products Hi-Level Analysis IDL Shell Browser Users

  3. OVSA Expansion Software and Data Handling 23-Oct-10 GH/JM+NJIT OVSA-specific CASPER-based Miriad-based RHESSI-based Monitor and Control Operator DSPU Antennas, receivers, analog subsystems NJIT Data Packaging Processor Interim Data Base Data selection, averaging, reformatting & calibration Burst identification Tohban Light curve, spectra display Archive Databases ~6 GB/day Light curve, spectra generation Map generation Map display Quick look & metadata products Hi-Level Analysis IDL Shell Browser Users

  4. OVSA Real-time Data Handling 25-Apr-2011 Monitor and Control Operator Antennas, receivers, analog subsystems Engineering Data Base State Frame Backend Correlator Data Packaging Processor Interim Data Base

  5. OVSA Real-time Data Handling 25-Apr-2011 Monitor and Control Operator Antennas, receivers, analog subsystems Engineering Data Base State Frame Backend Correlator 4 external interfaces Data Packaging Processor Interim Data Base

  6. OVSA Real-time Data Handling 25-Apr-2011 Monitor and Control Operator Antennas, receivers, analog subsystems State Frame Engineering Data Base Backend Correlator Data Packaging Processor 4 external interfaces Interim Data Base

  7. Digital Packaging Processor ACC State Frame Correlator Start / End Scan Cmds Scan-independent Calibration Parms Scan Parameters Frame parameters <P>, <P2> Correlations Frame status report DPP Miriad-format Interim Data Base

  8. DPP-Correlator Interface • 4096 x 2 x16^2 visibility components • 4096 x 2 x 16 <P2> values • 4-byte Floating point ? •  9 MB / integration  450 MB/s • Dedicated 10 Gb Ethernet link(s) ? • Interface architecture driven by correlator design

  9. DPP State Frame Interface • Specifics TBD • DPP will assume ‘header’ parameters are stable during scan • Otherwise DPP reads state frame every ½ second • Assume state frame has flags indicating update state • DPP updates state frame with processing status • ISSUE: Should RFI statistics be ignored, written to state frame, or included in IDB?

  10. DPP – ACC Interface • Low data volume • Shared Ethernet line • ACC issues start scan, end scan commands • ACC provides scan-independent calibration parameters (or should these be in state frame?)

  11. DPP – Interim Data Base Interface • DPP writes directly to dual-port IDB disk • DPP writes data in a Miriad-compatible format • Science frame: ~1 MB  1.4 MB/s  60 GB/day (0.7 second, 500 science channels, 2 polarizations, 2 byte data, 16^2 visibility components, x2 overhead) • IDB disk is also accessible to a data analysis platform

  12. DPP – Processing Tasks (1) • Stage 1 – Every integration interval • Evaluate kurtosis data to identify RFI-affected subbands as a function of frequeny only. • Combine with pre-flagged subbands to generate a destination vector for each subband • Apply complex gains at subband level ?? • Average subband data into science frequency bands • Save 1st 3 moments of averages. • Save RFI statistics ??

  13. DPP Processing Tasks (2) • Stage 2 Processing – Every science frame • Convert antenna-based flags (e.g. slewing) from state frame to baseline-based, frequency-independent flags • Apply time-dependent complex gains if available • Apply baseline corrections • Apply non-linearity corrections • Correct for attenuator settings • OPTIONAL – correct for spectral simultaneity

  14. DPP Processing Tasks (3) • Stage 3 processing - every science frame: • Convert visibility, uv and analysis-relevant state-frame data to Miriad format • Write science frame to IDB • Send DPP status to state frame

  15. DPP - Implementation • Original concept was to follow FASR plan for a cluster-based DPP • Estimate processing requirements for EOVSA at ~100 MIPS = 1/60 of FASR requirements • Implementation will be based on a single multi-core machine • Software organization will be compatible with migration to a cluster if necessary

  16. DPP Software Architecture Interim Database ACC State Frame Correlator DPP Coordination Task I/O, data assembly, no processing per se C1 Pointers within shared memory Header Processing Stage 1 Processing Stage 2 Processing Stage 3 Processing C2 C3, C4 C2 C2 Conventional, time-independent processing tasks Cn = core within quad core processor

  17. DPP Next Steps • Agreement on approach • Detailed definition of interfaces • Definition of processing algorithms • Machine selection and purchase • Development platform? • Language selection (Fortran + ?) • Test data sets? • Early timing tests

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