• Computer Science, Engineering
  • Published in ArXiv 2019

Adaptive Precision CNN Accelerator Using Radix-X Parallel Connected Memristor Crossbars

@article{Lee2019AdaptivePC,
  title={Adaptive Precision CNN Accelerator Using Radix-X Parallel Connected Memristor Crossbars},
  author={Jaeheum Lee and Jason K. Eshraghian and Kyoung-Rok Cho and Kamran Eshraghian},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.09395}
}
Neural processor development is reducing our reliance on remote server access to process deep learning operations in an increasingly edge-driven world. By employing in-memory processing, parallelization techniques, and algorithm-hardware co-design, memristor crossbar arrays are known to efficiently compute large scale matrix-vector multiplications. However, state-of-the-art implementations of negative weights require duplicative column wires, and high precision weights using single-bit… CONTINUE READING

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References

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SHOWING 1-10 OF 39 REFERENCES

Analog Weights in ReRAM DNN Accelerators

  • 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS)
  • 2019
VIEW 1 EXCERPT

A study on object detection method from manga images using CNN

  • 2018 International Workshop on Advanced Image Technology (IWAIT)
  • 2018
VIEW 1 EXCERPT

Binary Weighted Memristive Analog Deep Neural Network for Near-Sensor Edge Processing

  • 2018 IEEE 18th International Conference on Nanotechnology (IEEE-NANO)
  • 2018
VIEW 1 EXCERPT

Deep Learning towards Mobile Applications

Ji Wang, Bokai Cao, +3 authors Xiaomin Zhu
  • 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)
  • 2018
VIEW 1 EXCERPT