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article · 2014

FLAP: Tool to generate CUDA code from sequential C code

Erika Hernández-Rubio, Amilcar Meneses‐Viveros, Pedro M. Cortes Perez, Sergio D. Hernandez Zavala, Hector M. Martinez Rios

Cited by 0Abstract and details only

Abstract

The GPU usage has increased in the high performance computing applications. However, still programming tools required to facilitate the development of programs for GPUs. It is well known that the loops in sequential programs are potential sources of parallelization. Three types of FOR-loops have been identified that can be mapped to CUDA kernel: single loops, nested loops and loops involving reduction operations. These loops can be mapped to CUDA kernels using patterns. In this work we present FLAP, a tool to generate CUDA parallel code from sequential C code. This tool uses these patterns to generate parallel code CUDA. We present some tests to show the performance of the code that generates FLAP.

Cite this paper

APA 7

Hernández-Rubio, E., Meneses‐Viveros, A., Perez, P. M. C., Zavala, S. D. H., & Rios, H. M. M. (2014). FLAP: Tool to generate CUDA code from sequential C code. https://doi.org/10.1109/conielecomp.2014.6808564

MLA 9

Hernández-Rubio, Erika, et al. “FLAP: Tool to generate CUDA code from sequential C code.” vol. 794, 2014, pp. 35–40, https://doi.org/10.1109/conielecomp.2014.6808564.

Chicago

Hernández-Rubio, Erika, Amilcar Meneses‐Viveros, Pedro M. Cortes Perez, Sergio D. Hernandez Zavala, and Hector M. Martinez Rios. 2014. “FLAP: Tool to generate CUDA code from sequential C code.” https://doi.org/10.1109/conielecomp.2014.6808564.

Harvard

Hernández-Rubio, E. et al. (2014) ‘FLAP: Tool to generate CUDA code from sequential C code’. Available at: https://doi.org/10.1109/conielecomp.2014.6808564.

BibTeX
@article{hernandezrubio2014flap,
  title = {{FLAP: Tool to generate CUDA code from sequential C code}},
  author = {Hernández-Rubio, Erika and Meneses‐Viveros, Amilcar and Perez, Pedro M. Cortes and Zavala, Sergio D. Hernandez and Rios, Hector M. Martinez},
  volume = {794},
  pages = {35--40},
  year = {2014},
  doi = {10.1109/conielecomp.2014.6808564}
}

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