EasyNUSC: An Efficient Heterogeneous Computing Framework for Non-uniform Sampling Two-Dimensional Convolution Applications

Yu Lu, Ce Yu, Jian Xiao 0001, Hao Wang, Hao Fu, Shanjiang Tang, Bo Kang, Gang Zheng. EasyNUSC: An Efficient Heterogeneous Computing Framework for Non-uniform Sampling Two-Dimensional Convolution Applications. In Weizhi Meng 0001, Rongxing Lu, Geyong Min, Jaideep Vaidya, editors, Algorithms and Architectures for Parallel Processing - 22nd International Conference, ICA3PP 2022, Copenhagen, Denmark, October 10-12, 2022, Proceedings. Volume 13777 of Lecture Notes in Computer Science, pages 707-721, Springer, 2022. [doi]

@inproceedings{LuYXWFTKZ22,
  title = {EasyNUSC: An Efficient Heterogeneous Computing Framework for Non-uniform Sampling Two-Dimensional Convolution Applications},
  author = {Yu Lu and Ce Yu and Jian Xiao 0001 and Hao Wang and Hao Fu and Shanjiang Tang and Bo Kang and Gang Zheng},
  year = {2022},
  doi = {10.1007/978-3-031-22677-9_38},
  url = {https://doi.org/10.1007/978-3-031-22677-9_38},
  researchr = {https://researchr.org/publication/LuYXWFTKZ22},
  cites = {0},
  citedby = {0},
  pages = {707-721},
  booktitle = {Algorithms and Architectures for Parallel Processing - 22nd International Conference, ICA3PP 2022, Copenhagen, Denmark, October 10-12, 2022, Proceedings},
  editor = {Weizhi Meng 0001 and Rongxing Lu and Geyong Min and Jaideep Vaidya},
  volume = {13777},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-031-22677-9},
}