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PDL-Tiny

A minimal version of Perl Data Language and a test bench to develop a new PDL::NG core

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NOTE: I had envisioned a PDL::Tiny module which encompassed a minimalist core of PDL::NG (Next Gen) capability. However, on reading more about other Tiny modules, it appears that this usage is not consistent with the Tiny manifesto.

Consequently, the actual module naming is still TBD but the project is still PDL-Tiny.

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The PDL-Tiny project has a number of goals:

  1. To provide KISS capability for perl computation with PDL compatibility
  2. To architect and implement a new new PDL::NG ("next generation") core
  3. To support rapid updates and releases to speed developement
  4. To refine the definition of PDL::Tiny and PDL:NG requirements

Some general directions for PDL-Tiny (and PDL:NG) implementation:

  1. Use "modern" perl5 OO support with Moo
  • Maintain interoperability with new p5 OO development
  • Smooth compatibility with perl6
  1. Decompose PDL functionality into Roles
  • Roles would allow expression of PDL::NG features
  • Cross-cutting concerns could be implemented separately
  • Using roles means you could load just the features you need saving memory and reducing complexity
  • Maybe use Roles applied to objects as basis for JIT computation and performance optimization
  1. Should interoperate with PDL-2.x
  • Could we use 'handles' to delegate to PDL-2.x?
  • That would allow gradual development for the new features
  • Allow for interoperability, test ability, maybe regression and verification
  1. We could start with a perl-only implementation
  • This gives the outline of the implementation
  • Features first and then performance
  • Using PDL-2.x delegation to get performance
  • Migrate to new C/XS performance as available
  1. Unify Perl OO layer with C/XS computation layer
  • Provide symmetric operation from C or Perl (similar to Prima)
  • Provide a C FFI for PDL::NG to enable use from multiple languages/libraries
  • Propose using the C Object System (COS).
  1. Improved types support
  • All standard atomic types (NumPy and Python set as a start)
  • All OpenGL data types
  • Support N-D arrays of structures
  • Support more flexible indexing (e.g. strings, field names,...)
  • Support metadata for objects, and dimensions/axes:
    • Units
    • Axis types (row, col, x, y) or labels for improved threading control/syntax
    • Model after HDF5

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