Constructing Neuronal Network Models in Massively Parallel Environments

Constructing Neuronal Network Models in Massively Parallel Environments

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of...

Massively parallel simulation of brain-scale neuronal network models

Biologically detailed computational models of large-scale neuronal networks have now become feasible due to the development of increasingly powerful massively parallel supercomputers. We report here about the methodology involved in simulation of very large neuronal networks. Using conductance-based multicompartmental model neurons based on Hodgkin-Huxley formalism, we simulate a neuronal netwo...

An End-User Programming System for Constructing Massively Parallel Simulations

This dissertation presents Kedama, a programming system for end-users, in particular the children at the school students’ age, to enable construction of massively parallel simulations. Kedama allows the user to construct massively parallel simulations in a highly interactive graphical environment. A user-written program can be modified dynamically so that the user can explore the problem domain...

Stochastic Network Problems: Massively Parallel Solution

Massively Parallel Simulation of Business Process Models

Business Process Reengineering has emerged as a model-ing and analysis methodology for making the organization of an enterprise more eecient. For the purpose of reengi-neering, a business process model (BPM) has to be developed , the evaluation of which in almost any case demands simulation. Even for enterprises of moderate size, the BPMs tend to become prohibitively complex, precluding a seque...