Associative networks have a number of properties, including a rapid, compute efficient best-match and intrinsic fault tolerance, that make them ideal for many applications. However, large networks can be slow to emulate because of their storage and bandwidth requirements. In this chapter we present a simple but effective model of association and then discuss a performance analysis we have done in implementing this model on a single high-end PC workstation, a PC cluster, and FPGA hardware. © 2006 Springer.
CITATION STYLE
Hammerstrom, D., Gao, C., Zhu, S., & Butts, M. (2006). FPGA implementation of very large associative memories application to automatic speech recognition. In FPGA Implementations of Neural Networks (pp. 167–195). Springer US. https://doi.org/10.1007/0-387-28487-7_6
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