Artificial neural network acceleration on FPGA using custom instruction

@article{Santos2011ArtificialNN,
  title={Artificial neural network acceleration on FPGA using custom instruction},
  author={Patrick Santos and David Ouellet-Poulin and Daniel Shapiro and Miodrag Bolic},
  journal={2011 24th Canadian Conference on Electrical and Computer Engineering(CCECE)},
  year={2011},
  pages={000450-000455}
}
In this paper, we present the acceleration of a pre-trained feedforward artificial neural network executing on a NIOS II processor. Without the use of hardware acceleration, a feedforward artificial neural network spends much of its execution time on the calculation of the activation function between layers, in this case, the hyperbolic tangent function. A speedup of 4.36 was achieved via a custom instruction approximating the value of tanh(x) through the use of a range addressable lookup table… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-8 OF 8 CITATIONS

ASIPs for artificial neural networks

  • 2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)
  • 2011
VIEW 3 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

Exploring the Tradeoffs of Application-Specific Processing

  • IEEE Journal on Emerging and Selected Topics in Circuits and Systems
  • 2018

Approximation of hyperbolic tangent activation function using hybrid methods

  • 2013 8th International Workshop on Reconfigurable and Communication-Centric Systems-on-Chip (ReCoSoC)
  • 2013
VIEW 2 EXCERPTS
CITES RESULTS & METHODS

References

Publications referenced by this paper.
SHOWING 1-10 OF 14 REFERENCES

FPGA Implementation of Artificial Neurons: Comparison study

  • 2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications
  • 2008
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Oct.) Implementation of a fast artificial neural network library (FANN)

S. Nissen
  • 2003
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Efficient hardware implementation of the hyperbolic tangent sigmoid function

  • 2009 IEEE International Symposium on Circuits and Systems
  • 2009
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

High Speed VLSI Implementation of the Hyperbolic Tangent Sigmoid Function

  • 2008 Third International Conference on Convergence and Hybrid Information Technology
  • 2008
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Tanh approximation custom instruction for NIOS II. [Online]. Available: http://opencores.org/project,tanhapprox IEEE CCECE

P. Santos, D. Poulin
  • 2011
VIEW 1 EXCERPT

A low cost microcontroller implementation of neural network based hurdle avoidance controller for a car-like robot

  • 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE)
  • 2010
VIEW 1 EXCERPT

Application and Comparison of BP Neural Network Algorithm in MATLAB

  • 2010 International Conference on Measuring Technology and Mechatronics Automation
  • 2010
VIEW 1 EXCERPT

Hyperbolic tangent. [Online]. Available: http://mathworld.wolfram.com/ HyperbolicTangent.html

E. Weisstein
  • 2010