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.
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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
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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
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