latest

Release history

0.6.0 (unreleased)

0.5.0 (February 12, 2019)

Added

  • Allow LIF.min_voltage to have effect. The exact minimum voltage on the chip is highly affected by discritization (since the chip only allows minimum voltages in powers of two), but this will at least provide something in the ballpark. (#169)
  • Population spikes can now be used to send information more efficiently to the chip. Population spikes are necessary for larger models like those using CIFAR-10 data. (#161)

Changed

  • PES learning in Nengo Loihi more closely matches learning in core Nengo. (#139)
  • Learning in the emulator more closely matches learning on hardware. (#139)
  • The neurons used to transmit decoded values on-chip can be configured. By default, we use ten pairs of heterogeneous neurons per dimension. (#132)
  • Internal classes and functions have been reorganized and refactored. See the pull request for more details. (#159)
  • Simulator now gives a warning if the user requests a progress bar, instead of an error. This avoids potential problems in nengo_gui and elsewhere. (#187)
  • Nengo Loihi now supports NxSDK version 0.8.0. Versions 0.7.0 and 0.7.5 are still supported. (#188)

Fixed

  • We integrate current (U) and voltage (V) more accurately now by accounting for rounding during the decay process. This integral is used when discretizing weights and firing thresholds. This change significantly improves accuracy for many networks, but in particular dynamical systems like integrators. (#124, #114)
  • Ensure things in the build and execution happen in a consistent order from one build/run to the next (by using OrderedDict, which is deterministic, instead of dict, which is not). This makes debugging easier and seeding consistent. (#151)
  • Probes that use snips on the chip (when running with precompute=False) now deal with negative values correctly. (#169, #141)
  • Filtering for probes on the chip is guaranteed to use floating-point now (so that the filtered output is correct, even if the underlying values are integers). (#169, #141)
  • Neuron (spike) probes can now be filtered with synapse objects. (#182, #183)

0.4.0 (December 6, 2018)

Added

  • Added version tracking to documentation.

Changed

  • An error is now raised if a learning rule is applied to a non-decoded connection. (#103)
  • Switched documentation to new nengo-sphinx-theme. (#143)

Fixed

  • Snips directory included when pip installing nengo-loihi. (#134)
  • Closing nengo_loihi.Simulator will now close all the inner sub-simulators as well. (#102)

0.3.0 (September 28, 2018)

Added

  • Models can now use the nengo.SpikingRectifiedLinear neuron model on both the emulator and hardware backends.
  • Models can now run with different dt values (the default is 0.001, or 1 millisecond).
  • Added support for Distributions on Connection transforms.

Changed

  • Now compatible with NxSDK 0.7. We are currently not supporting older versions of NxSDK, but may in the future.
  • Models will not be precomputed by default. To precompute models, you must explicitly pass precompute=True to nengo_loihi.Simulator.
  • Models that do not run any objects on Loihi will raise an error.
  • Ensemble intercept values are capped to 0.95 to fix issues with the current discretization method.

Fixed

  • Tuning curves now take into account the Loihi discretization, improving accuracy on most models.
  • PES learning can now be done with multidimensional error signals.
  • Manually reset spike probes when Simulator is initialized.
  • Several fixes to filtering and connecting between objects on and off chip.

0.2.0 (August 27, 2018)

First public alpha release of Nengo Loihi! If you have any questions, please ask on our forum and if you run into any issues let us know.

0.1.0 (July 4, 2018)

Pre-alpha release of Nengo Loihi for testing at the 2018 Telluride neuromorphic engineering conference. Thanks to all participants who tried out this early version of Nengo Loihi and provided feedback.