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NeuroPipe-Chip: A digital neuro-processor for spiking neural networks.

T Schoenauer1, S Atasoy, N Mehrtash

  • 1Inst. of Microelectron., Technische Univ. Berlin.

IEEE Transactions on Neural Networks
|February 5, 2008
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Summary

We developed NeuroPipe-Chip, a novel neuro-processor, to accelerate complex Spiking Artificial Neural Networks (SANNs). This hardware significantly improves SANN computation speed, enabling real-time applications like image processing.

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Area of Science:

  • * Computer Engineering
  • * Artificial Intelligence
  • * Neuroscience

Background:

  • * Conventional hardware struggles with real-time computation of Spiking Artificial Neural Networks (SANNs).
  • * Existing platforms do not meet the demands for complex SANNs in real-world applications.
  • * There is a need for specialized hardware to accelerate SANN processing.

Purpose of the Study:

  • * To introduce novel on-chip concepts for accelerating SANN computation.
  • * To present the design and simulation of a prototype neuro-processor, NeuroPipe-Chip.
  • * To evaluate the performance of NeuroPipe-Chip for SANN acceleration.

Main Methods:

  • * Development of a neuro-processor (NeuroPipe-Chip) with two new on-chip acceleration concepts.
  • * Implementation of a prototype NeuroPipe-Chip.
  • * System simulation using a hardware description language (HDL) for performance evaluation.
  • * Fabrication of the NeuroPipe-Chip using Alcatel 0.35-μm digital CMOS technology.

Main Results:

  • * NeuroPipe-Chip operating at 100 MHz demonstrated over a two-order-of-magnitude improvement in SANN computation speed compared to an Alpha 500 MHz workstation.
  • * The prototype approaches real-time processing for SANNs involving approximately 10^6 neurons.
  • * The hardware structure was successfully simulated, validating the design.

Conclusions:

  • * NeuroPipe-Chip effectively accelerates the computation of complex Spiking Artificial Neural Networks.
  • * The developed neuro-processor enables SANNs to meet real-time requirements for demanding tasks.
  • * This accelerator facilitates real-world applications, including real-time image processing, using complex SANNs.