Recurrent Neural Networks Hardware Implementation on FPGA

Y. Bengio, P. Simard, and P. Frasconi, “Learning long-term dependencies with gradient descent is difficult,” IEEE Trans. on Neural Networks , vol. 5, no. 2, pp. 157–166, 1994

1994

Earlier work this paper cites.

S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural computation , vol. 9, no. 8, pp. 1735–1780, 1997

1997

Earlier work this paper cites.

F. Gers, J. Schmidhuber et al. , “Recurrent nets that time and count,” in Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on , vol. 3. IEEE, 2000, pp. 189–194

2000

Earlier work this paper cites.

A. Graves and J. Schmidhuber, “Framewise phoneme classification with bidirectional lstm and other neural network architectures,” Neural Networks , vol. 18, no. 5, pp. 602–610, 2005

2005

Earlier work this paper cites.

C. M. Bishop, “Pattern recognition and machine learning,” pp. 225–284, 2006

2006

Earlier work this paper cites.

C. Farabet, B. Martini, P. Akselrod, S. Talay, Y. LeCun, and E. Culurciello, “Hardware accelerated convolutional neural networks for synthetic vision systems,” in Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on . IEEE, 2010, pp. 257–260

2010

Earlier work this paper cites.

C. Farabet, B. Martini, B. Corda, P. Akselrod, E. Culurciello, and Y. LeCun, “Neuflow: A runtime reconfigurable dataflow processor for vision,” in IEEE Comp. Conf. on CVPRW . IEEE, 2011, pp. 109–116

2011

Earlier work this paper cites.

A. Graves, A.-r. Mohamed, and G. Hinton, “Speech recognition with deep recurrent neural networks,” in IEEE Int. Conf. on ICASSP , 2013, pp. 6645–6649

2013

Earlier work this paper cites.

A. Dundar, J. Jin, V. Gokhale, B. Krishnamurthy, A. Canziani, B. Martini, and E. Culurciello, “Accelerating deep neural networks on mobile processor with embedded programmable logic,” in Neural information processing systems conference (NIPS) , 2013

2013

Earlier work this paper cites.

R. Tavcar, J. Dedic, D. Bokal, and A. Zemva, “Transforming the lstm training algorithm for efficient fpga-based adaptive control of nonlinear dynamic systems,” Informacije Midem-Journal of Microelectronics Electronic Components and Materials , vol. 43, no. 2, pp. 131–138, 2013

2013

Cited alongside, same era.

I. Sutskever, O. Vinyals, and Q. V. Le, “Sequence to sequence learning with neural networks,” in Advances in neural information processing systems , 2014, pp. 3104–3112

2014

Cited alongside, same era.

K. Cho, B. Van Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio, “Learning phrase representations using rnn encoder-decoder for statistical machine translation,” EMNLP , 2014

2014

Cited alongside, same era.

W. Zaremba, I. Sutskever, and O. Vinyals, “Recurrent neural network regularization,” arXiv preprint arXiv:1409.2329 , 2014

Original

2014

Cited alongside, same era.

A. Dundar, J. Jin, V. Gokhale, B. Martini, and E. Culurciello, “Memory access optimized routing scheme for deep networks on a mobile coprocessor,” in High Performance Extreme Computing Conference (HPEC), 2014 IEEE . IEEE, 2014, pp. 1–6

2014

Later among the works it cites.

V. Gokhale, J. Jin, A. Dundar, B. Martini, and E. Culurciello, “A 240 g-ops/s mobile coprocessor for deep neural networks,” in IEEE Conf. on CVPRW, 2014 . IEEE, 2014, pp. 696–701

2014

Later among the works it cites.

Zedboard Product Brief , Avnet, Nov. 2014. [Online]. Available: http://zedboard.org/sites/default/files/product_briefs/PB-AES-Z7EV-7Z020_G-v12.pdf

Original

2014

Later among the works it cites.

W. Byeon, M. Liwicki, and T. M. Breuel, “Scene analysis by mid-level attribute learning using 2d lstm networks and an application to web-image tagging,” Pattern Recognition Letters , vol. 63, pp. 23–29, 2015

2015

Closest in time.