Prototyping a Biologically Plausible Neuron Model on a Heterogeneous CPU-FPGA Board

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Prototyping a Biologically Plausible Neuron Model on a Heterogeneous CPU-FPGA Board

Conference Paper (2019)

Author(s)

Kaleb Alfaro-Badilla (Instituto Tecnologico de Costa Rica)

Alfonso Chacon-Rodriguez (Instituto Tecnologico de Costa Rica)

Georgios Smaragdos (Erasmus MC)

Christos Strydis (Erasmus MC)

Andres Arroyo-Romero (Instituto Tecnologico de Costa Rica)

Javier Espinoza-Gonzalez (Instituto Tecnologico de Costa Rica)

Carlos Salazar-Garcia (Instituto Tecnologico de Costa Rica)

Affiliation

External organisation

High level synthesis Spiking neural networks Biologically accurate neural networks models Hardware-software co-design Heterogeneous systems Systems on chip

DOI related publication

https://doi.org/10.1109/LASCAS.2019.8667538 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:d7e086d5-f805-4176-89f6-6a08b672fa8f

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Publication Year

2019

Language

English

Affiliation

External organisation

Article number

8667538

Pages (from-to)

5-8

Publisher

IEEE

ISBN (electronic)

9781728104522

Event

10th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2019 (2019-02-24 - 2019-02-27), Armenia, Colombia

Downloads counter

77

Abstract

A heterogeneous hardware-software system implemented on an Avnet ZedBoard Zynq SoC platform, is proposed for the computation of an extended Hodgkin Huxley (eHH), biologically plausible neural model. SoC's ARM A9 is in charge of handling execution of a single neuron as defined in the eHH model, each with a O(N) computational complexity, while the computation of the gap-junctions interactions for each cell is offloaded on the SoC's FPGA, cutting its O(N²) complexity by exploiting parallel-computing hardware techniques. The proposed hw-sw solution allows for speed-ups of about 18 times visa-vis à vectorized software implementation on the SoC's cores, and is comparable to the speed of the same model optimized for a 64-bit Intel Quad Core i7, at 3.9GHz.