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UID:submissions.supercomputing.org_SC22_sess274_rpost174@linklings.com
SUMMARY:PDTgcomp: Compilation Framework for Data Transformation Kernels on
  GPU
DESCRIPTION:Posters, Research Posters\n\nPDTgcomp: Compilation Framework f
 or Data Transformation Kernels on GPU\n\nNguyen, Becchi\n\nData transforma
 tion tasks - such as encoding, decoding, parsing, and conversion between c
 ommon data formats - are at the core of many data analytics, data processi
 ng and scientific applications. This has led to the development of custom 
 software libraries and hardware implementations targeting popular data tra
 nsformations. By accelerating specific transformations, however, these sol
 utions suffer from  lack of generality.  On the other hand, a generic and 
 programmable data processing engine might support a wide range of data tra
 nsformations, but do so at the cost of reduced performance compared to cus
 tom, algorithm-specific solutions. \n\nIn this work, we aim to bridge this
  gap between generality and performance. To this end, we provide a compila
 tion framework that transparently converts data transformation tasks expre
 ssed using pushdown transducers into efficient GPU code.\n\nRegistration C
 ategory: Tech Program Reg Pass, Exhibits Reg Pass
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