Models (sanafe.models)

This page documents every pipeline model available in SANA-FE. It begins with the framework attributes shared by all models, followed by a section for each model listing its model-specific attributes.

Framework attributes

These attributes are accepted by every pipeline model in SANA-FE. They control shared behavior such as energy/latency reporting, hardware unit selection, and update scheduling, and apply equally to built-in and plugin models.

Attribute	Description
connections_out	(int) Connections outgoing from a neuron (deprecated)
dendrite_hw_name	(str) Unique name of the dendrite H/W unit.
energy_access_neuron	(float) Energy cost for a soma to access a neuron (J).
energy_message_in	(float) Energy cost of receiving a spike message (J).
energy_message_out	(float) Energy cost of sending a spike message (J)
energy_process_spike	(float) Energy cost for one synapse look-up/access (J).
energy_spike_out	(float) Energy cost for a soma to spike (J).
energy_update	(float) Energy cost of updating a dendrite (s)
energy_update_neuron	(float) Energy cost for a soma to update (J).
force_update	(bool) Force updates every time-step.
latency_access_neuron	(float) Latency cost for a soma to access a neuron (s).
latency_message_in	(float) Latency cost of receiving a spike message (s).
latency_message_out	(float) Latency cost of sending a spike message (s)
latency_process_spike	(float) Latency cost for one synapse look-up/access (s).
latency_spike_out	(float) Latency cost for a soma to spike (s).
latency_update	(float) Latency cost of updating a dendrite (s)
latency_update_neuron	(float) Energy cost for a soma to update (s).
model	(str) Unique model name, either built-in or plugin.
plugin	(str) Plug-in library path.
soma_hw_name	(str) Unique name of the soma H/W unit.
synapse_hw_name	(str) Unique name of the synapse H/W unit.

accumulator

(none)

accumulator_with_delay

(none)

current_based

Attribute	Description
d	(float) Time-steps that a spike is delayed.
delay	(float) Time-steps that a spike is delayed.
w	(float) Synaptic weight associated with connection.
weight	(float) Synaptic weight associated with connection.

input

Attribute	Description
poisson	(float) Randomized Poisson input encoding, i.e., random > poisson: spike, else no spike.
rate	(float) Rate-based input encoding.
spikes	(list[bool]) A per-time-step spike-train.

leaky_integrate_and_fire

Attribute	Description
bias	Bias current applied every step: v[t+1] = bias + v[t]*leak_decay + u[t]
force_potential	(no description)
force_update	(bool) Force soma to update every step, regardless of inputs.
force_update_every_timestep	(bool) Force soma to update every step, regardless of inputs.
leak_decay	(float) Decay term applied every step: v[t+1] = bias + v[t]*leak_decay + u[t]
log_u	(bool) Record input current (u) for Loihi soma.
noise	(str) Noise source. Only file-based noise stream supported
noise_bits	(int) The number of noise bits simulated.
refractory_delay	(int) The number of refractory steps after a spike, default=0.
reset	(float) The potential to reset to after a spike. Default=0.0
reset_mode	(str) The type of reset to apply on spikes [none/soft/hard/saturate]. Default=hard
reverse_reset	(float) The potential to reset to after a reverse spike.
reverse_reset_mode	(str) The type of reset to apply on negative/reverse spikes [none/soft/hard/saturate]. Default=None
reverse_threshold	(float) Fires when V < reverse_threshold, then V <- f(reverse_reset_mode, reverse_reset).
threshold	(float) Fires when V > threshold, then V <- f(reset_mode, reset).

taps

Attribute	Description
space_constants	(list[float]) List of RC line space constants, N-1 in total.
taps	(int) Number of N dendritic ‘taps’ or compartments.
time_constants	(list[float]) List of RC line time constants, one per tap.

truenorth

Attribute	Description
bias	Additive bias current applied every step.
leak	(float) Subtractive leak term applied every step
leak_towards_zero	(bool) Leak towards zero if true, leak away otherwise.
random_mask	(int) Positive mask to apply to randomly generated noise.
reset	(float) The potential to reset to after a spike. Default=0.0
reset_mode	(str) The type of reset to apply on spikes [none/soft/hard/saturate]. Default=hard
reverse_reset	(float) The potential to reset to after a reverse spike.
reverse_reset_mode	(str) The type of reset to apply on negative/reverse spikes [none/soft/hard/saturate]. Default=None
reverse_threshold	(float) The potential at which a reverse spike is triggered.
threshold	(float) The potential at which a spike is triggered.