High Performance Computing Resources for Parallel Simulations and Data

SUMMARY

This workshop is intended for neuroscientists who need to use high
performance computing (HPC) resources for computationally intensive tasks
such as large modeling projects or analysis of neuroimaging data. It will
examine resources offered by the Neuroscience Gateway Portal (NSG
https://www.nsgportal.org/) and The Human Brain Project's High Performance
Analytics and Computing Platform (HPAC
https://hbp-hpc-platform.fz-juelich.de/). The workshop will combine
hands-on instruction on how to use NSG with didactic presentations by NSG
and HPAC developers and discussions with experienced users of these
resources.

The registration deadline for this workshop is Friday Oct. 12,
but you should sign up early because space is limited. See

https://neuron.yale.edu/neuron/static/courses/nsg2018/nsg2018.html

for more information and a link to the registration form.

OVERVIEW OF NSG AND HPAC

NSG eliminates most administrative and technical barriers, providing free
CPU time to users, and easy access to widely used software that currently
includes BluePyOpt, Brian, CARLsim, DynaSim, EEGLAB, Freesurfer, GENESIS,
Human Neocortical Neuroserver (HNN), Large Scale Neural Modeling Simulator
(LSNM), MATLAB, MOOSE, NEST, NetPyNE, NEURON, Octave, PyNN, Python, R,
TensorFlow, and the Virtual Personalized Multimodal Connectome Pipeline.
NSG's web-based interface simplifies the tasks of uploading models or data,
specifying job parameters, monitoring job status, and storing and
retrieving output data.

HPAC provides extensive HPC support for the HBP community. This includes
developing and providing the hardware and software infrastructure required
for large scale simulations, data management and analysis, visualization,
and managing the complex workflows involved in performing these tasks. The
workshop will combine hands-on instruction on how to use NSG with didactic
presentations by NSG and HPAC developers and discussions with experienced
users of these resources.