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@inproceedings{MMBS14,
  title={ADHA: Automatic Data layout framework for Heterogeneous Architectures},
  bib2html_dl_pdf={http://arxiv.org/pdf/1407.4859.pdf},
  author={Majeti, Deepak and Meel, Kuldeep S. and Barik, Raj and Sarkar, Vivek},
  booktitle=PACT,
  year={2014},
  month=aug,
  bib2html_pubtype={Refereed Conference},
  bib2html_rescat={Software Engineering},
  abstract={
    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.
  },
}