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Data layouts play a crucial role in determining the performance of a givenapplication running on a given architecture. Existing parallel programmingframeworks for both multicore and heterogeneous systems leave the onus ofselecting a data layout to the programmer. Therefore, shifting the burden ofdata layout selection to optimizing compilers can greatly enhance programmerproductivity and application performance. In this work, we introduce {\ADHA}: atwo-level hierarchal formulation of the data layout problem for modernheterogeneous architectures. We have created a reference implementation of ADHAin the Heterogeneous Habanero-C (H2C) parallel programming system. ADHA showssignificant performance benefits of up to 6.92$\times$ compared to manuallyspecified layouts for two benchmark programs running on a CPU+GPU heterogeneousplatform.

ADHA: Automatic Data layout framework for Heterogeneous Architectures