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  • 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
    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/ 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
        - (un)packing slices of fields (from)into the buffer
        - (un)packing subsets of cell values from the fields (from)into the buffer
    - 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/, 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.