Commit 979ee93b authored by Committed by Martin BauerBrowse files
Code generation for field serialization into buffers
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.