Capacitive Content-Addressable Memory: A Highly Reliable and Scalable Approach to Energy-Efficient Parallel Pattern Matching Applications

Nuo Xiu, Yiming Chen, Guodong Yin, Xiaoyang Ma, Huazhong Yang, Sumitha George, Xueqing Li. Capacitive Content-Addressable Memory: A Highly Reliable and Scalable Approach to Energy-Efficient Parallel Pattern Matching Applications. In Yiran Chen, Victor V. Zhirnov, Avesta Sasan, Ioannis Savidis, editors, GLSVLSI '21: Great Lakes Symposium on VLSI 2021, Virtual Event, USA, June 22-25, 2021. pages 479-484, ACM, 2021. [doi]

@inproceedings{XiuCYMYGL21,
  title = {Capacitive Content-Addressable Memory: A Highly Reliable and Scalable Approach to Energy-Efficient Parallel Pattern Matching Applications},
  author = {Nuo Xiu and Yiming Chen and Guodong Yin and Xiaoyang Ma and Huazhong Yang and Sumitha George and Xueqing Li},
  year = {2021},
  doi = {10.1145/3453688.3461744},
  url = {https://doi.org/10.1145/3453688.3461744},
  researchr = {https://researchr.org/publication/XiuCYMYGL21},
  cites = {0},
  citedby = {0},
  pages = {479-484},
  booktitle = {GLSVLSI '21: Great Lakes Symposium on VLSI 2021, Virtual Event, USA, June 22-25, 2021},
  editor = {Yiran Chen and Victor V. Zhirnov and Avesta Sasan and Ioannis Savidis},
  publisher = {ACM},
  isbn = {978-1-4503-8393-6},
}