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DEF-G: Declarative Framework for GPU Environment

Robert Senser, Tom Altman
Department of Computer Science and Engineering, University of Colorado Denver, Denver, CO
The 2013 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’13), 2013

@article{senser2013def,

   title={DEF-G: Declarative Framework for GPU Environment},

   author={Senser, Robert and Altman, Tom},

   year={2013}

}

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DEF-G is a declarative language and framework for the efficient generation of OpenCL GPU applications. Using our proof-of-concept DEF-G implementation, run-time and lines-of-code comparisons are provided for three well-known algorithms (Sobel image filtering, breadth-first search and all-pairs shortest path), each evaluated on three different platforms. The DEF-G declarative language and corresponding OpenCL kernels generated complete OpenCL applications in C/C++. Initial lines-of-code comparison demonstrates that the DEF-G applications require significantly less coding than hand-written CPU-side OpenCL applications. The run-time results demonstrate very similar performance characteristics compared to the hand-written applications. We also provide useful observations, which we found to be noteworthy for practitioners, concerning the effectiveness of certain OpenCL API options.
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