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Real-time olivary neuron simulations on dataflow computing machines

G. Smaragdos ; C. Davies ; C. Strydis ; Ioannis Sourdis (Institutionen för data- och informationsteknik, Datorteknik (Chalmers)) ; Catalin Ciobanu (Institutionen för data- och informationsteknik, Datorteknik (Chalmers)) ; O. Mencer ; C.I. De Zeeuw
Lecture Notes in Computer Science: 29th International Supercomputing Conference, ISC 2014; Leipzig; Germany; 22 June 2014 through 26 June 2014 (0302-9743). Vol. 8488 (2014), p. 487-497.
[Konferensbidrag, refereegranskat]

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.



Denna post skapades 2015-05-06. Senast ändrad 2016-09-14.
CPL Pubid: 216652

 

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