NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliv...

General-Purpose Computation without General-Purpose Processors

A General Purpose Network Simulation Tool

This paper presents NESSY (NEtwork Simulation SYstem): a whole environment for performance evaluation of communication networks. The modeling methodology proposed by NESSY is mainly based upon the OO (ObjectOriented) techniques and the FDT (Formal Description Technique). With OO approach the network model is a collection of objects. FDT is used to describe the objects that model the network com...

A VML Based Implementation of a Neural Network Library on General Purpose Parallel Processors

Vectorized Algorithms for Spiking Neural Network Simulation

High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of B...