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Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model
The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale neural network simulations in real time and with low power consumption. Expand
Accuracy and Efficiency in Fixed-Point Neural ODE Solvers
Simulation of neural behavior on digital architectures often requires the solution of ordinary differential equations (ODEs) at each step of the simulation. Expand
Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ODEs.
Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types. The main reasons areExpand
PyNN on SpiNNaker Software 2015.004
Spiking neural networks for computer vision
We use structural synaptic plasticity as a possible mechanism whereby biological vision systems may learn the statistics of their inputs without supervision, pointing the way to engineered vision systems with similar online learning capabilities. Expand
Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations
We investigate approaches to improving the accuracy of reduced-precision fixed-point arithmetic types, using examples in an important domain for numerical computation in neuroscience: the solution of ordinary differential equations. Expand
26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2
Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP isExpand
Event-based computation: unsupervised elementary motion decomposition
We show that neurons become sensitised in an unsupervised manner to bars moving in various directions through local learning mechanisms and an interplay between lateral excitation and inhibition. Expand
Behavioral Learning in a Cognitive Neuromorphic Robot: An Integrative Approach
We present here a learning system using the iCub humanoid robot and the SpiNNaker neuromorphic chip to solve the real-world task of object-specific attention. Expand