Code Generation: A Strategy for Neural Network Simulators
Neuroinformatics
(2010) 8, no. 3 (9).
Abstract
We demonstrate a technique for the design of neural network simulation
software, runtime code generation. This technique can be used to give
the user complete flexibility in specifying the mathematical model for
their simulation in a high level way, along with the speed of code
written in a low level language such as C++. It can also be used to
write code only once but target different hardware platforms, including
inexpensive high performance graphics processing units (GPUs). Code
generation can be naturally combined with computer algebra systems to
provide further simplification and optimisation of the generated code.
The technique is quite general and could be applied to any simulation
package. We demonstrate it with the "Brian" simulator
(http://www.briansimulator.org).
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Related software
A Python simulator for spiking neural networks.
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