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  1. Mar 07, 2019
  2. Feb 26, 2019
  3. Feb 18, 2019
  4. Feb 03, 2019
  5. Jan 24, 2019
  6. Jan 23, 2019
    • Martin Bauer's avatar
      waLBerla codegeneration improved · 7ac04691
      Martin Bauer authored
      - removed warnings from generated code
      - made generated code string deterministic, generating the same twice
        gives binary equally files now
      7ac04691
  7. Jan 09, 2019
  8. Nov 16, 2018
  9. Nov 14, 2018
    • Martin Bauer's avatar
      Pass field information (shape,stride) as single elements instead of arr · 490d6902
      Martin Bauer authored
      - small (length < 5) arrays with shape and stride information had to be
        memcpy'd to the GPU before every kernel call
      - instead of passing the information as arrays, the single elements are
        passed
      - leads to more function arguments, but simplifies GPU kernel calls
      
      -> changes in all backends required
      490d6902
  10. Nov 13, 2018
  11. Oct 29, 2018
  12. Oct 24, 2018
  13. Oct 23, 2018
  14. Oct 19, 2018
  15. Oct 18, 2018
  16. Oct 16, 2018
  17. Oct 13, 2018
  18. Oct 10, 2018
  19. Oct 02, 2018
  20. Apr 30, 2018
  21. Apr 27, 2018
  22. Apr 24, 2018
  23. Apr 13, 2018
  24. Apr 10, 2018
  25. Mar 06, 2018
  26. Jan 19, 2018
    • João Victor Tozatti Risso's avatar
      Code generation for field serialization into buffers · c7dcbf4a
      João Victor Tozatti Risso authored and Martin Bauer's avatar Martin Bauer committed
      Concept: Generate code involving the (un)packing of fields (from)to linear
      (1D) arrays, i.e. (de)serialization of the field values for buffered
      communication.
      
      A linear index is generated for the buffer, by inferring the strides and
      variables of the loops over fields in the AST. In the CPU, this information is
      obtained through the makeLoopOverDomain function, in
      pystencils/transformations/transformations.py. On CUDA, the strides of
      the fields (excluding buffers) are combined with the indexing variables to infer
      the indexing of the buffer.
      
      What is supported:
          - code generation for both CPU and GPU
          - (un)packing of fields with all the memory layouts supported by
          pystencils
          - (un)packing slices of fields (from)into the buffer
          - (un)packing subsets of cell values from the fields (from)into the buffer
      
      Limitations:
      
      - assumes that only one buffer and one field are being operated within
      each kernel, however multiple equations involving the buffer and the
      field are supported.
      
      - (un)packing multiple cell values (from)into the buffer is supported,
      however it is limited to the fields with indexDimensions=1. The same
      applies to (un)packing subset of cell values of each cell.
      
      Changes in this commit:
      
      - add the FieldType enumeration to pystencils/field.py, to mark fields
      of various types. This is replaces and is a generalization of the
      isIndexedField boolean flag of the Field class. For now, the types
      supported are: generic, indexed and buffer fields.
      
      - add the fieldType property to the Field class, which indicates the
      type of the field. Modifications were also performed to the member
      functions of the Field class to add this property.
      
      - add resolveBufferAccesses function, which replaces the fields marked
      as buffers with the actual field access in the AST traversal.
      
      Miscelaneous changes:
      
      - add blockDim and gridDim variables as CUDA indexing variables.
      c7dcbf4a
  27. Dec 11, 2017
  28. Oct 10, 2017