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GeNN
1.1
GPU enhanced Neuronal Networks (GeNN)
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| Contains the implementation of the Gaussian random number generator class randomGauss | |
| Random number generator for Gaussian random variable with mean 0 and standard deviation 1 | |
| Contains the implementation of the ISAAC random number generator class for uniformly distributed random numbers and for a standard random number generator based on the C function rand() | |
| Header file containing the class definition for a uniform random generator based on the ISAAC random number generator | |
| Contains three macros that allow simple bit manipulations on an (presumably unsigned) 64 bit integer | |
| Global header file containing a few global variables. Part of the code generation section | |
| This file contains the implementation of the CStopWatch class that provides a simple timing tool based on the system clock | |
| This header file contains the definition of the CStopWatch class that implements a simple timing tool using the system clock | |
| Header file that contains the class (struct) definition of neuronModel for defining a neuron model and the class definition of NNmodel for defining a neuronal network model. Part of the code generation and generated code sections | |
| Contains a template function for string conversion from const char* to C++ string | |
| This file contains standard utility functions provide within the NVIDIA CUDA software development toolkit (SDK). The remainder of the file contains a function that defines the standard neuron models | |
| Functions for generating code that will run the neuron and synapse simulations on the CPU. Part of the code generation section | |
| Contains functions that generate code for CUDA kernels. Part of the code generation section | |
| Contains functions to generate code for running the simulation on the GPU, and for I/O convenience functions between GPU and CPU space. Part of the code generation section | |
| This file is part of a tool chain for running the classol/MBody1 example model | |
| This file is part of a tool chain for running the classol/MBody1 example model | |
| This file is part of a tool chain for running the classol/MBody1 example model | |
| This file is part of a tool chain for running the classol/MBody1 example model | |
| This file is part of a tool chain for running the classol/MBody1 example model | |
| This file generates the arrays needed for sparse connectivity. The connectivity is saved to a file for each variable and can then be read to fill the struct of connectivity | |
| This file is part of a tool chain for running the Izhikevich network model | |
| This file is part of a tool chain for running the classIzh/Izh_sparse example model | |
| This file contains the model definition of HHVClamp model. It is used in both the GeNN code generation and the user side simulation code. The HHVClamp model implements a population of unconnected Hodgkin-Huxley neurons that evolve to mimick a model run on the CPU, using genetic algorithm techniques | |
| Main entry point for the GeNN project demonstrating realtime fitting of a neuron with a GA running mostly on the GPU | |
| Main entry point for the classol (CLASSification in OLfaction) model simulation. Provided as a part of the complete example of simulating the MBody1 mushroom body model | |
| Header file containing global variables and macros used in running the HHVClamp/VClampGA model | |
| Implementation of the classol class | |
| Header file containing the class definition for classol (CLASSification OLfaction model), which contains the methods for setting up, initialising, simulating and saving results of a model of the insect mushroom body | |