Abstract

It takes more than a good algorithm to achieve high performance: inner-loop performance and data locality are also important. Tiling is a well-known method for parallelization and for improving data locality. However, tiling has the potential of being even more beneficial. At the finest granularity, it can be used to guide register allocation and instruction scheduling; at the coarsest level, it can help manage magnetic storage media. It also can be useful in overlapping data movement with computation, for instance by prefetching data from archival storage, disks and main memory into cache and registers, or by choreographing data movement between processors. Hierarchical tiling is a framework for applying both known tiling methods and new techniques to an expanded set of uses. It eases the burden on several compiler phases that are traditionally treated separately, such as scalar replacement, register allocation, generation of message passing calls, and storage mapping. By explicitly ...

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