Real-time olivary neuron simulations on dataflow computing machines
Paper i proceeding, 2014

The Inferior-Olivary nucleus (ION) is a well-charted brain region, heavily associated with the sensorimotor control of the body. It comprises neural cells with unique properties which facilitate sensory processing and motor-learning skills. Simulations of such neurons become rapidly intractable when biophysically plausible models and meaningful network sizes (at least in the order of some hundreds of cells) are modeled. To overcome this problem, we accelerate a highly detailed ION network model using a Maxeler Dataflow Computing Machine. The design simulates a 330-cell network at real-time speed and achieves maximum throughputs of 24.7 GFLOPS. The Maxeler machine, integrating a Virtex-6 FPGA, yields speedups of ×92-102, and ×2-8 compared to a reference-C implementation, running on a Intel Xeon 2.66GHz, and a pure Virtex-7 FPGA implementation, respectively.


G. Smaragdos

Erasmus Universiteit Rotterdam

C. Davies

Maxeler Technologies

C. Strydis

Erasmus Universiteit Rotterdam

Ioannis Sourdis

Chalmers, Data- och informationsteknik, Datorteknik

Catalin Ciobanu

Chalmers, Data- och informationsteknik, Datorteknik

O. Mencer

Maxeler Technologies

Imperial College London

C.I. De Zeeuw

Erasmus Universiteit Rotterdam

Netherlands Institute for Neuroscience NIN - KNAW

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 8488 487-497
978-3-319-07517-4 (ISBN)


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