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@bcumming bcumming released this 04 Mar 17:46
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v0.2
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Arbor library version 0.2, tagged as v0.2

Arbor is a library for implementing performance portable network simulations of multi-compartment neuron models.

An installation guide and library documentation are available online at Read the Docs.

Submit a ticket if you have any questions or want help.

Some key features include:

  • Optimized back ends for CUDA, KNL, AVX2, ARM NEON intrinsics.
  • Asynchronous spike exchange that overlaps compute and communication.
  • Efficient sampling of voltage and current on all back ends.
  • Efficient implementation of all features on GPU.
  • Reporting of memory and energy consumption (when available on platform).
  • An API for addition of new cell types, e.g. LIF and Poisson spike generators.

Change Log

Changes since v0.1:

  • A new Hines matrix solver back end for the GPU that parallelises over cell
    branches, not cells, to increase the amount of parallelism. See #631.
  • Support for describing and simulating electrical gap junctions. See #661 #686.
  • An additional library libarborenv is now installed with useful
    helper functionality for managing the environment (e.g. detecting the number of available CPU cores). See #679.
  • Detection and allocation of GPUs to MPI ranks on systems with more than one GPU per node in libarborenv. See #659 and #654.
  • The miniapp example was removed and replaced with a simple single cell model that shows how to use morphologies. See #703 and #710.
  • Support for ARM NEON intrinsics. See #698.
  • Basic Python support. Full Python support is slated for v0.3. See #668.

Contributors

Nora Abi Akar
John Biddiscombe
Benjamin Cumming
Felix Huber
Marko Kabic
Vasileios Karakasis
Wouter Klijn
Anne Küsters
Alexander Peyser
Stuart Yates

Citation

DOI

Nora Abi Akar, John Biddiscombe, Benjamin Cumming, Felix Huber, Marko Kabic, Vasileios Karakasis, Wouter Klijn, Anne Küsters, Alexander Peyser, Stuart Yates. (2019, March 4). arbor-sim/arbor: Arbor Library v0.2 (Version v0.2). Zenodo. http://doi.org/10.5281/zenodo.2583709

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