Training itself: Mixed-signal training acceleration for memristor-based neural network

Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC

Volumn , Issue , 2014, Pages 361-366

  Li, Boxun ^a   Wang, Yuzhi ^a   Weng, Yu ^a   Chen, Yiran ^b   Yang, Huazhong ^a  

^a TSINGHUA UNIVERSITY   (China)

^b UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

Memristor; Neural Network; Training

Indexed keywords

DATA PROCESSING APPLICATIONS; DIGITAL COMPUTING SYSTEMS; HARDWARE REALIZATION; MEMRISTOR; ORDERS OF MAGNITUDE; RECOGNITION ACCURACY; STOCHASTIC GRADIENT DESCENT ALGORITHM; TRAINING ACCELERATION;

COMPUTER AIDED DESIGN; DATA PROCESSING; ENERGY EFFICIENCY; NETWORK ARCHITECTURE; NEURAL NETWORKS; PASSIVE FILTERS; PERSONNEL TRAINING;

MEMRISTORS;

EID: 84897828040     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ASPDAC.2014.6742916     Document Type: Conference Paper

References (18)

1. Jeffrey Dean et al. Large scale distributed deep networks. In P. Bartlett, F. C. N. Pereira, C. J. C. Burges, L. Bottou, and K. Q. Weinberger, editors, Advances in Neural Information Processing Systems 25, pages 1232-1240, 2012.
2. Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, and Doug Burger. Neural acceleration for general-purpose approximate programs. In Proceedings of the 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture.
3. Russell Beale and Tom Jackson. Neural Computing-an introduction. CRC Press, 2010.
4. Dmitri B Strukov, Gregory S Snider, Duncan R Stewart, and R. Stanley Williams. The missing memristor found. Nature, 453(7191):80-83, 2008.
5. Beiye Liu, Miao Hu, Hai Li, Zhi-Hong Mao, Yiran Chen, Tingwen Huang, and Wei Zhang. Digital-assisted noise-eliminating training for memristor crossbar-based analog neuromorphic computing engine. In Proceedings of the 50th Annual Design Automation Conference, 2013.
6. Miao Hu, Hai Li, Qing Wu, and Garrett S Rose. Hardware realization of bsb recall function using memristor crossbar arrays. In Proceedings of the 49th Annual Design Automation Conference, 2012.
7. Li Boxun, Shan Yi, Hu Miao, Wang Yu, Chen Yiran, and Yang Huazhong. Memristor-based approximated computation. In Proceedings of ISLPED 2013.
8. Rafael Menéndez De Llano and José Luis Bosque. Study of neural net training methods in parallel and distributed architectures. Future Generation Computer Systems, 26(2):267-275, 2010.
9. Simon S Haykin, Simon S Haykin, Simon S Haykin, and Simon S Haykin. Neural networks and learning machines, volume 3. Prentice Hall New York, 2009.
10. Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow, Andrew Ng, and Quoc V Le. On optimization methods for deep learning. In Proceedings of the 28th International Conference on Machine Learning (ICML-11), pages 265-272, 2011.
11. Sieu D Ha and Shriram Ramanathan. Adaptive oxide electronics: A review. Journal of Applied Physics, 110(7):071101-071101, 2011.
12. Wei Yi, Frederick Perner, et al. Feedback write scheme for memristive switching devices. Applied Physics A, 102:973-982, 2011.
13. Robinson E Pino, Hai Li, Yiran Chen, Miao Hu, and Beiye Liu. Statistical memristor modeling and case study in neuromorphic computing. In Design Automation Conference (DAC), 2012 49th ACM/EDAC/IEEE, pages 585-590. IEEE, 2012.
14. G. Khodabandehloo, M. Mirhassani, and M. Ahmadi. Analog implementation of a novel resistive-type sigmoidal neuron. TVLSI, 20(4):750-754, april 2012.
15. Rainer Gemulla, Erik Nijkamp, Peter J Haas, and Yannis Sismanis. Large-scale matrix factorization with distributed stochastic gradient descent. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 69-77. ACM, 2011.
16. Yann LeCun and Corinna Cortes. The mnist database of handwritten digits, 1998.
17. Geoffrey E Hinton and Ruslan R Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, 2006.
18. Intel. Intel math kernel library. http://software.intel.com/en-us/ intelmkl/.