ADHA: Automatic Data layout framework for Heterogeneous Architectures

Deepak Majeti, Kuldeep S. Meel, Rajkishore Barik, Vivek Sarkar
Rice University
arXiv:1407.4859 [cs.DC], (18 Jul 2014)


   title={ADHA: Automatic Data layout framework for Heterogeneous Architectures},

   author={Majeti, Deepak and Meel, Kuldeep S and Barik, Rajkishore and Sarkar, Vivek},

   journal={arXiv preprint arXiv:1407.4859},



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Data layouts play a crucial role in determining the performance of a given application running on a given architecture. Existing parallel programming frameworks for both multicore and heterogeneous systems leave the onus of selecting a data layout to the programmer. Therefore, shifting the burden of data layout selection to optimizing compilers can greatly enhance programmer productivity and application performance. In this work, we introduce {ADHA}: a two-level hierarchal formulation of the data layout problem for modern heterogeneous architectures. We have created a reference implementation of ADHA in the Heterogeneous Habanero-C (H2C) parallel programming system. ADHA shows significant performance benefits of up to 6.92x compared to manually specified layouts for two benchmark programs running on a CPU+GPU heterogeneous platform.
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