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Performance Analysis and Parallelization Strategies in Neuron Simulation Codes

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Brain-Inspired Computing (BrainComp 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8603))

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Abstract

An important activity within the Human Brain Project (HBP) is to analyse and optimize the two main neuron simulation codes to improve their scalability and adapt them to efficiently work under an interactive supercomputing usage pattern. One application was already MPI + OpenMP while the other was pure MPI. We describe the analyses performed with the BSC tools and the initial efforts to hybridize the codes for better matching multicore architectures and to introduce the malleability that will be needed to operate under dynamic resource allocation environments of the future.

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References

  1. NEST Initiative, June 2014. http://www.nest-initiative.org/

  2. NEURON|for empirically-based simulations of neurons and networks of neurons, June 2014. http://www.neuron.yale.edu/neuron/

  3. Paraver|BSC-CNS, June 2014. http://www.bsc.es/computer-sciences/performance-tools/paraver

  4. Cluster Analysis|BSC-CNS, June 2014. http://www.bsc.es/computer-sciences/performance-tools/clustering

  5. Folding|BSC-CNS, June 2014. http://www.bsc.es/computer-sciences/performance-tools/folding

  6. The OmpSs Programming Model|Programming Models@BSC, June 2014. http://pm.bsc.es/ompss/

  7. Dynamic Load Balance|Programming Models@BSC, June 2014. http://pm.bsc.es/dlb

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Author information

Authors and Affiliations

  1. Barcelona Supercomputing Center (BSC-CNS), Barcelona, Spain

    Victor Lopez, Marçal Sola & Jesus Labarta

Authors
  1. Victor Lopez
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  2. Marçal Sola
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  3. Jesus Labarta
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Corresponding author

Correspondence to Victor Lopez .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Calabria, Arcavacada di Rende, Italy

    Lucio Grandinetti

  2. Jülich Supercomputing Centre, Jülich, Germany

    Thomas Lippert

  3. Computing Science, University of Groningen Institute for Mathematics &, Groningen, The Netherlands

    Nicolai Petkov

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© 2014 Springer International Publishing Switzerland

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Lopez, V., Sola, M., Labarta, J. (2014). Performance Analysis and Parallelization Strategies in Neuron Simulation Codes. In: Grandinetti, L., Lippert, T., Petkov, N. (eds) Brain-Inspired Computing. BrainComp 2013. Lecture Notes in Computer Science(), vol 8603. Springer, Cham. https://doi.org/10.1007/978-3-319-12084-3_12

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  • DOI: https://doi.org/10.1007/978-3-319-12084-3_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12083-6

  • Online ISBN: 978-3-319-12084-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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