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@INPROCEEDINGS{Klijn:841438,
      author       = {Klijn, Wouter and Cumming, B. and Yates, S. and Karakasis,
                      V. and Peyser, Alexander},
      title        = {{N}est{MC}: {A} morphologically detailed neural network
                      simulator for modern high performance computer
                      architectures},
      reportid     = {FZJ-2017-08484},
      year         = {2017},
      abstract     = {NestMC is a new multicompartment neural network simulator
                      currently under development as a collaboration between the
                      Neuroscience SimLab at the Forschungszentrum Jülich,
                      Barcelona Supercomputing Center and the Swiss National
                      Supercomputing Center under the aegis of the NEST
                      Initiative. NestMC will enable new scales and classes of
                      morphologically detailed network simulations on current and
                      future supercomputing architectures.A number of "many-core"
                      architectures such as GPU and Intel Xeon Phi based systems
                      are currently available, to optimally use these emerging
                      architecture new approaches in software development and
                      algorithm design are needed. NestMC is being written
                      specifically with this in mind; it aims to be a flexible
                      platform for neural network simulation, while keeping
                      interoperability with models and workflows of NEST and
                      NEURON.The improvements in performance and flexibility in
                      themselves will enable a variety of novel experiments, but
                      the design is not finalised, and is driven by the
                      requirements of the neuroscientific community. The prototype
                      is open source (1) and we invite you to have a look. We are
                      interested in your ideas for features which will make new
                      science possible: we ask you to think outside of the box and
                      build this next generation neurosimulator together with
                      us.What directions do you want us to go in?• Simulate
                      large morphological detailed networks for longer time
                      scales: Study of slow developing phenomena.• Reduce the
                      time to solution: Perform more repeat experiments for
                      increased statistical power.• Create high performance
                      interfaces with other software: Perform online statistical
                      analysis and visualization of your running models, study the
                      brain at multiple scales with specialized tools, or embed
                      detailed networks in physically modelled animals.•
                      Optimize dynamic data structures for models with
                      time-varying number of neurons, synapses and compartments:
                      simulate neuronal development, healing after injury and age
                      related neuronal degeneration.Do you have other great ideas?
                      Let us know!},
      month         = {Feb},
      date          = {2017-02-08},
      organization  = {HBP student conference 2017, Vienna
                       (Austria), 8 Feb 2017 - 10 Feb 2017},
      subtyp        = {Other},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / SMHB - Supercomputing and Modelling for the
                      Human Brain (HGF-SMHB-2013-2017) / HBP SGA1 - Human Brain
                      Project Specific Grant Agreement 1 (720270) / SLNS - SimLab
                      Neuroscience (Helmholtz-SLNS)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-Juel1)HGF-SMHB-2013-2017 /
                      G:(EU-Grant)720270 / G:(DE-Juel1)Helmholtz-SLNS},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/841438},
}