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Arbor v0.10.0

Authors: Cumming, Benjamin; Yates, Stuart; Hater, Thorsten; Lu, Han; Huisman, Brent; Wouter, Klijn; Bösch, Fabian; +3 Authors
Abstract

v0.10.0 Major Changes since v0.9.0 * Automatic network generation from high-level specifications.* Units at the user interface including scaling and conversion.* Morphologies are loaded through a unified interface; which produces a bundle of morphology, metadata, and segment tree. Internal Updates * Documentation overhaul* Python bindings offer type stubs; giving auto-completion and inline documentation in some editors/IDEs.* Performance improvements - Label resolution uses hashes instead of strings, saving memory, network traffic, and time. - Spike delivery is up to 30% faster leading to 10% end-to-end improvements in some cases (e.g. `example/brunel`) - Load balancing is faster and doesn't rely on MPI, leading to shorter setup times for large networks.* Fixes - Better support for source builds on MacOS (aarch64) - `modcc` no longer allows internal variables (`v`, `celsius`, ...) as `ASSIGNED` - Better support for raw (C++) mechanisms* MC cells renamed cable cells. Breaking changes * Return values of all morphology loaders have changed.* Raw (segment tree) loaders removed.* Support for Python 3.8 removed.* C++: Removed `simulation::inject_events`, use a generator instead. New Contributors * @ErbB4 made their first contribution in https://github.com/arbor-sim/arbor/pull/2271 Full Changelog: https://github.com/arbor-sim/arbor/compare/v0.9.0...v0.10.0

Keywords

Computational neuroscience, Simulation software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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