After the generation of search spaces, a single candidate layout is selected for each program part, resulting in a data layout for the entire program. A good overall data layout may require the remapping of arrays between program parts. The machine model uses the novel training set approach which determines the costs of arithmetic operations and simple communication patterns. In the proposed framework, instances of NP-complete problems are solved during the construction of candidate layout search spaces and the final selection of candidate layouts from each search space. A prototype of the data layout asistant tool has been implemented.
Experiments indicate that good data layouts can be determined efficiently.
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