dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference

Elias Trommer, Bernd Waschneck, Akash Kumar 0001. dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference. In IEEE/ACM International Conference On Computer Aided Design, ICCAD 2021, Munich, Germany, November 1-4, 2021. pages 1-9, IEEE, 2021. [doi]

@inproceedings{TrommerW021,
  title = {dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference},
  author = {Elias Trommer and Bernd Waschneck and Akash Kumar 0001},
  year = {2021},
  doi = {10.1109/ICCAD51958.2021.9643506},
  url = {https://doi.org/10.1109/ICCAD51958.2021.9643506},
  researchr = {https://researchr.org/publication/TrommerW021},
  cites = {0},
  citedby = {0},
  pages = {1-9},
  booktitle = {IEEE/ACM International Conference On Computer Aided Design, ICCAD 2021, Munich, Germany, November 1-4, 2021},
  publisher = {IEEE},
  isbn = {978-1-6654-4507-8},
}