Efficient simulation of large-scale spiking neuronal networks is important for neuroscientific research, and both the simulation speed and the time it takes to instantiate the network in computer memory are key factors. In recent years, hardware acceleration through highly parallel GPUs has become increasingly popular. Similarly, code generation approaches have been utilized to optimize software performance, albeit at the cost of repeated code regeneration and recompilation after modifications to the network model [1].To address the need for greater flexibility in iterative model changes, we propose a new method for creating network connections dynamically and directly in GPU memory. This method uses a set of commonly used high-level connec...
Detailed brain modeling has been presenting significant challenges to the world of high-performance ...
Biological neuronal networks models can be investigated with the NEST simulator (Gewaltig and Diesma...
Spiking neural network models are increasingly establishing themselves as an effective tool for simu...
Simulation speed matters for neuroscientific research: this includes not only how quickly the simula...
Simulation speed matters for neuroscientific research: this includes not only how fast the simulated...
Simulation speed matters for neuroscientific research: this includes not only how quickly the simula...
Simulations are an important tool for investigating brain function but large models are needed to fa...
Over the past decade there has been a growing interest in the development of parallel hardware syste...
Large-scale simulations of parts of the brain using detailed neuronal models to improve our understa...
© 2011 Jad Abi-SamraThe study of the structure and functionality of the brain has been ardently inve...
Current brain simulators do no scale linearly to realistic problem sizes (e.g. >100,000 neurons),...
Recent advances in the development of data structures to represent spiking neuron network models ena...
While neuromorphic systems may be the ultimate platform for deploying spiking neural networks (SNNs)...
Simulating biological neural networks is an important task for computational neuroscientists attempt...
Computational models whose organization is inspired by the cortex are increasing in both number and ...
Detailed brain modeling has been presenting significant challenges to the world of high-performance ...
Biological neuronal networks models can be investigated with the NEST simulator (Gewaltig and Diesma...
Spiking neural network models are increasingly establishing themselves as an effective tool for simu...
Simulation speed matters for neuroscientific research: this includes not only how quickly the simula...
Simulation speed matters for neuroscientific research: this includes not only how fast the simulated...
Simulation speed matters for neuroscientific research: this includes not only how quickly the simula...
Simulations are an important tool for investigating brain function but large models are needed to fa...
Over the past decade there has been a growing interest in the development of parallel hardware syste...
Large-scale simulations of parts of the brain using detailed neuronal models to improve our understa...
© 2011 Jad Abi-SamraThe study of the structure and functionality of the brain has been ardently inve...
Current brain simulators do no scale linearly to realistic problem sizes (e.g. >100,000 neurons),...
Recent advances in the development of data structures to represent spiking neuron network models ena...
While neuromorphic systems may be the ultimate platform for deploying spiking neural networks (SNNs)...
Simulating biological neural networks is an important task for computational neuroscientists attempt...
Computational models whose organization is inspired by the cortex are increasing in both number and ...
Detailed brain modeling has been presenting significant challenges to the world of high-performance ...
Biological neuronal networks models can be investigated with the NEST simulator (Gewaltig and Diesma...
Spiking neural network models are increasingly establishing themselves as an effective tool for simu...