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  1. SAFe Program
  2. SP-616

Improve Sparse Matrix Support in Yandasoft Regularised Solver

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    • Data Processing
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      The work is important in the context of SKA-scale profiling and comparisons and the applicability of a parallel solver to bandpass calibration.

      Enables end-to-end comparison of solvers

      Show
      The work is important in the context of SKA-scale profiling and comparisons and the applicability of a parallel solver to bandpass calibration. Enables end-to-end comparison of solvers
    • Hide
      • new solver supports sparse matrix format for reduced memory footprint
      • new solver has improved normal equation generation times
      • system demo at the earliest possible time with the aim of prioritising future work in the areas of optimisation and relevant test scenarios/data
      Show
      new solver supports sparse matrix format for reduced memory footprint new solver has improved normal equation generation times system demo at the earliest possible time with the aim of prioritising future work in the areas of optimisation and relevant test scenarios/data
    • 3
    • 3
    • 0
    • Team_YANDA
    • Sprint 5
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      sys demo presentation slides
      https://confluence.skatelescope.org/download/attachments/93226413/SystemDemo_Vitaliy.pdf?api=v2

      Show
      sys demo presentation slides https://confluence.skatelescope.org/download/attachments/93226413/SystemDemo_Vitaliy.pdf?api=v2
    • 8.5
    • Stories Completed, Outcomes Reviewed, Demonstrated, Satisfies Acceptance Criteria

    • PI24 - UNCOVERED

    • Team_YANDA

    Description

      Following earlier performance improvements building the equation is now becoming the computational bottleneck that should be addressed.

      Currently, the matrix values are stored in inefficient data structure (the map of map of matrixes with string keys) in building the equation, and then copied to the efficient solver sparse matrix when solving the equation. Bypassing this intermediate storage would reduce the memory footprint and computational cost.

      Further potential improvements should be investigated and benchmarked, such as a reported slow merge in the imager.

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          Feature - A Feature is a service that fulfills a stakeholder need. Each feature includes a benefit hypothesis and acceptance criteria, and is sized or split as necessary to be delivered by a single Agile Release Train (ART) in a Program Increment (PI). SP-462 Add SKA1-Low beam support to JACAL

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          Feature - A Feature is a service that fulfills a stakeholder need. Each feature includes a benefit hypothesis and acceptance criteria, and is sized or split as necessary to be delivered by a single Agile Release Train (ART) in a Program Increment (PI). SP-472 Parallelized Regularized Calibration Solver

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          split to

          Feature - A Feature is a service that fulfills a stakeholder need. Each feature includes a benefit hypothesis and acceptance criteria, and is sized or split as necessary to be delivered by a single Agile Release Train (ART) in a Program Increment (PI). SP-733 Yandasoft Regularised Bandpass Solver - robustness to spectral gaps

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          • Done
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                r.laing Laing, Robert
                m.dolensky Dolensky, Markus [X] (Inactive)
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                Feature Progress

                  Story Point Burn-up: (100.00%)

                  Feature Estimate: 3.0

                  IssuesStory Points
                  To Do00.0
                  In Progress   00.0
                  Complete1026.0
                  Total1026.0

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