Abstract. We consider the problem of automatically guiding program transformations for locality, despite incomplete information due to complicated program structures, changing target architectures, and lack of knowledge of the properties of the input data. Our system, the modal model of memory, uses limited static analysis and bounded runtime experimentation to produce performance formulas that can be used to make runtime locality transformation decisions. Static analysis is performed once per program to determine its memory reference properties, using modes, a small set of parameterized, kernel reference patterns. Once per architectural system, our system automatically performs a set of experiments to determine a family of kernel performance formulas. The system can use these kernel formulas to synthesize a performance formula for any program's mode tree. Finally, with program transformations represented as mappings between mode trees, the generated performance formulas can be used to guide transformation decisions.
The modal model of memory REF requires not only static analysis but also runtime experimentation (potentially thousands of experiments) in order to generate performance formulas.
A Modal Model of Memory
International Conference on Computational Science (1)
Computer Science