An energy-efficient VLSI architecture for pattern recognition via deep embedding of computation in SRAM

@article{Kong2014AnEV,
  title={An energy-efficient VLSI architecture for pattern recognition via deep embedding of computation in SRAM},
  author={Mingu Kong and Min-Sun Keel and Naresh R. Shanbhag and Sean Eilert and Ken Curewitz},
  journal={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2014},
  pages={8326-8330}
}
In this paper, we propose the concept of compute memory, where computation is deeply embedded into the memory (SRAM). This deep embedding enables multi-row read access and analog signal processing. Compute memory exploits the relaxed precision and linearity requirements of pattern recognition applications. System-level simulations incorporating various… CONTINUE READING