Architectures for high-performance FPGA implementations of neural models.

@article{Weinstein2006ArchitecturesFH,
  title={Architectures for high-performance FPGA implementations of neural models.},
  author={Randall K Weinstein and Robert H. Lee},
  journal={Journal of neural engineering},
  year={2006},
  volume={3 1},
  pages={21-34}
}
As the complexity of neural models continues to increase (larger populations, varied ionic conductances, more detailed morphologies, etc) traditional software-based models have difficulty scaling to reach the performance levels desired. This paper describes the use of FPGAs, or field programmable gate arrays, to easily implement a wide variety of neural models with the performance of custom analogue circuits or computer clusters, the reconfigurability of software, and at a cost rivalling… CONTINUE READING

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