Real-time olivary neuron simulations on dataflow computing machines
Paper in 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.
Author
G. Smaragdos
Erasmus University Rotterdam
C. Davies
Maxeler Technologies
C. Strydis
Erasmus University Rotterdam
Ioannis Sourdis
Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)
Catalin Ciobanu
Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)
O. Mencer
Maxeler Technologies
Imperial College London
C.I. De Zeeuw
Erasmus University 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 LNCS 487-497978-3-319-07517-4 (ISBN)
Subject Categories
Human Computer Interaction
DOI
10.1007/978-3-319-07518-1_34
ISBN
978-3-319-07517-4