1. 28 Apr, 2018 1 commit
  2. 27 Apr, 2018 3 commits
  3. 18 Apr, 2018 2 commits
  4. 13 Apr, 2018 1 commit
  5. 10 Apr, 2018 7 commits
  6. 06 Mar, 2018 1 commit
  7. 31 Jan, 2018 1 commit
  8. 19 Jan, 2018 1 commit
    • João Victor Tozatti Risso's avatar
      Code generation for field serialization into buffers · 979ee93b
      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.
      979ee93b
  9. 11 Dec, 2017 1 commit
  10. 03 Dec, 2017 2 commits
  11. 11 Oct, 2017 1 commit
  12. 10 Oct, 2017 2 commits
  13. 09 Oct, 2017 1 commit
    • Martin Bauer's avatar
      Vectorization & Type system overhaul · ea847bc5
      Martin Bauer authored
      - first vectorization tests are running
      - type system: use memoized getTypeOfExpression
      - casts are done using sp.Function('cast')
      - C backend adapted for vectorization support
      - AST nodes can required optional headers
      ea847bc5
  14. 26 Sep, 2017 2 commits
  15. 25 Sep, 2017 1 commit
  16. 21 Sep, 2017 1 commit
  17. 26 Jul, 2017 2 commits
  18. 01 Jul, 2017 1 commit
    • Martin Bauer's avatar
      Kerncraft coupling · 3b4deebe
      Martin Bauer authored
      - pystencils can create now a non-compilable kernel that can be
        analyzed by kerncraft
      3b4deebe
  19. 30 Mar, 2017 1 commit
  20. 24 Mar, 2017 2 commits
  21. 19 Mar, 2017 1 commit
  22. 16 Mar, 2017 2 commits
  23. 14 Mar, 2017 1 commit
    • Martin Bauer's avatar
      pystencils: fields can now contain structs · ec3faf51
      Martin Bauer authored
      - this extension is necessary for more generic boundary treatment
      - cells can now be structs, i.e. contain different data types
      - instead of having numeric index dimensions, one can use the index per cell to adress struct elements
      ec3faf51
  24. 13 Mar, 2017 1 commit
    • Martin Bauer's avatar
      pystencils: Cleaned up type system · c8b455fe
      Martin Bauer authored
      - use data type class consistently instead of strings (in TypedSymbol, Field and jit module)
      - new datatype class is based on numpy types with additional specifier information (const and restrict)
      - translation between data type class and other modules (numpy, ctypes)
      c8b455fe
  25. 02 Mar, 2017 1 commit