SRAM-based efficiency memory model for quantized convolutional neural networks
Author:
Affiliation:
1. Chiba University,Graduate School of Science and Engineering,Chiba,Japan,263-8522
2. Chiba University,Graduate School of Engineering,Chiba,Japan,263-8522
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10226627/10226615/10226859.pdf?arnumber=10226859
Reference7 articles.
1. SRAM voltage scaling for energy-efficient convolutional neural networks
2. Bit Error Tolerance of a CIFAR-10 Binarized Convolutional Neural Network Processor
3. Significance Driven Hybrid 8T-6T SRAM for Energy-Efficient Synaptic Storage in Artificial Neural Networks
4. Gradient-based learning applied to document recognition
5. Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
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