Abstract
Graphics Processing Units (GPU) have established themselves as effective platforms for high-performance computing. Utilizing the power of these devices usually requires significant changes to existing codes or the development of a completely new solution. In this paper, we survey approaches that we believe are the most promising in reducing the complexity of programming or porting codes to GPUs. We also focus our presentation on our refactoring tool developed for this purpose, called ExtractKernel, which transforms existing C loops into code that can execute on the GPU.
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Damevski, K. (2012). Tool Support for Efficient Programming of Graphics Processing Units. In: Toni, B., Williamson, K., Ghariban, N., Haile, D., Xie, Z. (eds) Bridging Mathematics, Statistics, Engineering and Technology. Springer Proceedings in Mathematics & Statistics, vol 24. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4559-3_9
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DOI: https://doi.org/10.1007/978-1-4614-4559-3_9
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