A highly scalable restricted Boltzmann machine FPGA implementation

FPL 09: 19th International Conference on Field Programmable Logic and Applications

Volumn , Issue , 2009, Pages 367-372

  Kim, Sang Kyun ^a   McAfee, Lawrence C ^a   McMahon, Peter L ^a   Olukotun, Kunle ^a  

^a Stanford University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BELIEF NETWORKS; BUILDING BLOCKES; EMBEDDED HARDWARE; FPGA IMPLEMENTATIONS; LARGER NETWORKS; MACHINE-LEARNING; NEW TOOLS; NOVEL ARCHITECTURE; PIPELINED ARCHITECTURE; RESTRICTED BOLTZMANN MACHINE; SOFTWARE IMPLEMENTATION;

ROBOT LEARNING;

FIELD PROGRAMMABLE GATE ARRAYS (FPGA);

EID: 70449805398     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FPL.2009.5272262     Document Type: Conference Paper

References (11)

1. G. Hinton, S. Osindero, and Y. Teh, "A fast learning algorithm for deep belief nets." Neural Computation, vol. 18, pp. 1527-1554, 2006.
2. G. W. Taylor, G. E. Hinton, and S. T. Roweis, "Modeling human motion using binary latent variables," in Advances in Neural Information Processing Systems 19. MIT Press, 2007, pp. 1345-I352.
3. C. Cox and E. Blanz, "Ganglion - a fast field-progammable gate array implementation ofa connectionist classifier," IEEE J. Solid-State Circuits, vol. 28, no. 3, pp. 288-299, 1992.
4. P. Lysaght, J. Stockwood, J. Law, and D. Girma, "Artificial neural network implementation on a fine-grained fpga," Field-Programmable Logic Architectures, Synthesis and Applications, vol. 849, pp. 421-431,1994.
5. J. Zhu and P. Sutton, "Fpga implementations of neural networks: a survey ofa decade of progress," in Proc. 13th International Conference on Field-Programmable Logic and Applications, Sept. 2003, pp. 1062-1066.
6. D. Ly and P. Chow, "A high-performance fpga architecture for restricted boltzmann machines," in Proc. of the ACM/SIGDA International Symposium on Field Programmable Gate Arrays, Feb. 2009, pp. 73-82.
7. H. Lee, C. Ekanadham, and A. Ng, "Sparse deep belief net model for visual area v2," in Advances in Neural Information Processing Systems 20. MIT Press, 2008, pp. 873-880.
8. L. Zadeh, "Fuzzy logic neural networks and soft computing," Communications of the ACM, vol. 37, no. 3, pp. 77-84, 1994.
9. J. Holt and T. Baker, "Back propagation simulations using limited precision calculations," in Proc. International Joint Conference on Neural Networks, vol. 2, July 1991, pp. 121-126.
10. H. Amin, K. Curtis, and B. Hayes-Gill, "Piecewise linear approximation applied to nonlinear function of a neural network," IEE Proc.-Circuits Devices Syst., vol. 144, no. 6, pp. 313-317, 1997.
11. T. Tkacik, "A hardware random number generator," in Cryptographic Hardware and Embedded Systems - CHES 2002, ser. Lecture Notes in Computer Science, vol. 2523, Jan. 2003, pp. 450-453.