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Vectorization-Aware Loop Optimization With User-Defined Code Transformations

2017 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER)(2017)

Cited 9|Views18
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Abstract
The cost of maintaining an application code would significantly increase if the application code is branched into multiple versions, each of which is optimized for a different architecture. In this work, default and vector versions of a real-world application code are refactored to be a single version, and the differences between the versions are expressed as userdefined code transformations. As a result, application developers can maintain only the single version, and transform it to its vector version just before the compilation. Although code optimizations for a vector processor are sometimes different from those for other processors, application developers can enjoy the performance of the vector processor without increasing the code complexity. Evaluation results demonstrate that vectorization-aware loop optimization for a vector processor can be expressed as user-defined code transformation rules, and thereby significantly improve the performance of a vector processor without major code modifications.
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