Abstract
The continuous advances in VLSI technologies, computer architecture and software development tools make it difficult to find the adequate implementation platform of an ANN for a given application. This paper describes HANNA, a software tool designed to automate the generation of hardware prototypes of MLP and MLP-like neural networks over FPGA devices. Coupled with traditional Matlab®/Simulink® environments the generated model can be synthesized, downloaded to the FPGA and co-simulated with the software version to trade off area, speed and precision requirements. The tool and our design methodology are validated through two examples.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Omondi, A.F., Rajapakse, J.C.: Neural Networks in FPGAs. Proc. of the 9th Int. Conf. on Neural Information Processing 2, 954–959 (2002)
Densmore, D., Passerone, R.: A Platform-Based Taxonomy for ESL Design. IEEE Design & Test of computers 23(5), 359–374 (2006)
Xilinx Inc.: Xilinx System Generator v7.1 User Guide. Xilinx Inc. (2005), http://www.xilinx.com
Zhu, J., Sutton, P.: FPGA Implementations of Neural Networks - a Survey of a Decade of Progress. In: Proc. of 13th Int. Conf. on Field Programmable Logic and Applications, pp. 1062–1066 (2003)
Ramón, J.L., Sprekelsen, C., Marín, M.L., González-Ortín, M., Rubio, M.: Método de estudio de las frecuencias fundamentales y análisis espectrográfico de los dos primeros formantes de las vocales castellanas emitidas por cien sujetos normales. Acta Otorrinolaringológica Española 30, 399–414 (1986)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Garrigós, J., Martínez, J.J., Toledo, J., Ferrández, J.M. (2007). HANNA: A Tool for Hardware Prototyping and Benchmarking of ANNs. In: Mira, J., Álvarez, J.R. (eds) Nature Inspired Problem-Solving Methods in Knowledge Engineering. IWINAC 2007. Lecture Notes in Computer Science, vol 4528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73055-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-540-73055-2_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73054-5
Online ISBN: 978-3-540-73055-2
eBook Packages: Computer ScienceComputer Science (R0)