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Published April 29, 2022 | Version 4.7.1
Software Open

genn-team/genn: GeNN 4.7.1

Authors/Creators

  • 1. University of Sussex
  • 2. @Cyanapse
  • 3. @Mercateo
  • 4. Facebook
  • 5. QUBIX
  • 6. Institut de la Vision
  • 7. IRCN, UTokyo
  • 8. Janssen R&D
  • 9. Herr

Description

Release Notes for GeNN v4.7.1

This release fixes a plethora of issues found in the 4.7.0 release and also includes an optimisation which could be very beneficial for some classes of model.

Bug fixes
  1. Fixed issue meaning that manual changes to max synaptic row length (via SynapseGroup::setMaxConnections) were not detected and model might not be rebuilt. Additionally, reduce the strictness of checks in SynapseGroup::setMaxConnections and SynapseGroup::setMaxSourceConnections so maximum synaptic row and column lengths can be overridden when sparse connectivity initialisation snippets are in use as long as overriding values are larger than those provided by snippet (#515).
  2. Fixed issue preventing PyGeNN being built on Python 2.7 (#510)
  3. Fixed issue meaning that inSyn, denDelayInSyn and revInSynOutSyn variables were not properly zeroed during initialisation (or reinitialisation) of batched models (#509).
  4. Fixed issue where initialization code for synapse groups could be incorrectly merged (#508).
  5. Fixed issue when using custom updates on batched neuron group variables (#507).
  6. Fixed issue in spike recording system where some permutations of kernel and neuron population size would result in memory corruption (#502).
  7. Fixed (long-standing) issue where LLDB wasn't correctly invoked when running genn-buildmodel.sh -d on Mac (#518).
  8. Fixed issue where sparse initialisation kernels weren't correctly generated if they were only required to initialise custom updates (#517).
Optimisations
  1. Using synapse dynamics with sparse connectivity previously had very high memory requirements and poor performance. Both issues have been solved with a new algorithm (#511).

Files

genn-team/genn-4.7.1.zip

Files (2.1 MB)

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Additional details

Related works

Is supplement to
https://github.com/genn-team/genn/tree/4.7.1 (URL)