Editing intel/loihi

{{intel title|Loihi}}
{{chip
|chip type=neuromorphic chip
|name=Loihi
|no image=No
|designer=Intel
|manufacturer=Intel
|market=Artificial Intelligence
|first announced=September 25, 2017
|first launched=January, 2018
|process=14 nm
|transistors=2,070,000,000
|technology=CMOS
|die area=60 mm²
|max cpus=16,384
|v core min=0.50 V
|v core max=1.25 V
}}
'''Loihi''' (pronounced ''low-ee-hee'') is a [[neuromorphic chip|neuromorphic]] research test chip designed by [[Intel]] Labs that uses an asynchronous [[spiking neural network]] (SNN) to implement adaptive self-modifying event-driven fine-grained parallel computations used to implement learning and inference with high efficiency. The chip is a 128-neuromorphic cores [[many-core]] IC fabricated on Intel's [[14 nm process]].

The chip is named after the Loihi as a play-on-words - [[wikipedia:Lōʻihi Seamount|Loihi]] is an emerging Hawaiian submarine volcano that is set to surface one day.

== Overview ==
Announced in September 2017, Loihi is predominantly a research chip meaning performance characteristics are not guaranteed. Loihi consists of a asynchronous [[spiking neural network]] (SNN) meaning instead of manipulating signals, the chip sends spikes along activate synapses. Connections are asynchronous and highly timed based. Neuromorphic cores containing many neurons are interlinked and receive spikes from elsewhere in the network. When received spikes accumulate for a certain period of time and reach a set threshold, the core will fire off its own spikes to its connected neurons. Preceding spikes reinforce each other and the neuron connections while spikes that follows will inhibit the connection, declining the connectivity until all activities are halted.


The chip was initially tested and simulated using FPGAs. Actual silicon implementations arrived in late November. Loihi is fabricated on Intel's [[14 nm process]] and has a total of 130,000 artificial neurons and 130 million synapses. In addition to the 128 neuromorphic cores, there are 3 managing {{intel|Lakemont|l=arch|Lakemont cores}}.

== Architecture ==
The chip consists of a [[many-core]] mesh of 128 neuromorphic cores, three {{intel|Lakemont|l=arch|Lakemont x86 cores}} ({{intel|Quark}}), and an off-chip communication interface that allows the chip to scale out to many other chips in the four planar directions (as shown on the right). The implemented mesh protocol supports up to 4,096 on-chip cores and up to 16,384 chips.

:[[File:loihi mesh chips.png|500px]]

The chip itself implements of a fully asynchronous [[many-core]] [[mesh topology|mesh]] of 128 neuromorphic cores. It implements a [[spiking neural network]] (SNN) whereby at any given time one or more of the implemented neurons may send out an impulse (i.e., spike) to its neighbors though the directed links (synapses). All neurons have a local state with their own set of rules that affects their evolution and the timing of spike generation. Interaction is entirely asynchronous, sporadic, and independent of any other neuron on the network. Core-to-core communication is done in using packetized messages with write, read request, and read response messages for core management and [[x86]]-to-x86 messaging, spike messages, and barrier messages (for synchronization).
=== Neuromorphic Core ===
Loihi implements 128 neuromorphic cores, each containing 1,024 primitive spiking neural units grouped into tree-like structures in order to simplify the implementation. Each of those groups share the same [[fan-in]] and [[fan-out]] connections, configuration, and state variables in ten architectural memories.

Loihi implements a variant of the [[current-based synapse]] (CUBA) [[leaky integrate-and-fire neuron]] model with two internal state variables:

* Synaptic response current <math>u_i(t)</math> - the weighted sum of the input spikes and a constant bias
* Membrane potential <math>v_t(t)</math> - a leaky (i.e. weakens over time) spike potential function that sends out a spike when the potential passes the firing threshold

It's worth noting that since Loihi is a digital architecture, the above  continuous functions are approximated using a discrete timestep whereby all neurons maintain a timestemp synchronized throughout the entire chip. This is needed in order to enable well-defined behaviors.

==== Operation and Communication ====
The operation itself is fairly straightforward, once enough spikes accumulate and exceed the predefined threshold level, a spike message is created and sent out to various other groups in various destination cores. Loihi is actually the first neuromorphic chip to feature a fully integrated [[SNN]] meaning it can support unicast, multicast, broadcast, sparse network, variable synaptic formats (any weight precision 1-9 bits, +/-, etc..), and population-based hierarchical connectivity.

Communication is done by each of the cores independently iterating over each of their neuron groups and for every group that enters a firing state, the core generates a spike message that is distributed to all the other cores on the mesh that contain their synaptic fanouts. The iterations of all the groups by all the cores must be done within the same discrete timestamp. To ensure that all the spikes have made it to their destinations before the operation is repeated, Loihi sends out a synchronization message whereby any spikes in-flight are flushed in the first phase and in the second phase a timestep-advance notification is sent to all the cores to advance their timestamp to <math>t+1</math>, enabling them to proceed to update their internal groups.

:[[File:loihi spikes.gif|400px]]

It should be noted that Loihi supports a hierarchical network model which means it can exploits the localized sub-networks in the mesh in order to substantially reduce the chip-wide connectivity and synaptic resources required to map the networks.

==== Self-learning ====
Each core also contains a "learning engine" that can be programmed to adopt to the network parameters during operation such as the spike timings and their impact. This makes the chip more flexible as it allows various paradigms such as supervisor/non-supervisor and reinforcing/reconfigurablity without requiring any particular approach. The choice for higher flexibility is intentional in order to defer various architectural decisions that could be detrimental to research.

== Die ==
[[File:loihi floorplan.png|thumb|right|Floorplan]]
* [[14 nm process]]
* 2,070,000,000 transistors
**  128 neuromorphic cores + 3 x86 cores
* 60 mm² die size

: [[File:intel loihi die shot.png|650px]]

== Test board ==
Thought Intel didn't specify, the test board appears to feature four Loihi chips meaning the board has 512 neuromorphic cores and 524,288 neurons, all are fully integrated over the mesh.

:[[File:loihi neuromorphic-test-board.png|900px]]

== References ==
* Jim Held, Intel Fellow & Director Emerging Technologies Research, Intel Labs, HPC Developer Conference 2017 ("Leading The Evolution of Compute: Neuromorphic and Quantum Computing").
* Davies, Mike, et al. "Loihi: A Neuromorphic Manycore Processor with On-Chip Learning." IEEE Micro (2018).

== See also ==
* {{ibm|TrueNorth}}
back image	+
core voltage (max)	1.25 V (12.5 dV, 125 cV, 1,250 mV) +
core voltage (min)	0.5 V (5 dV, 50 cV, 500 mV) +
designer	Intel +
die area	60 mm² (0.093 in², 0.6 cm², 60,000,000 µm²) +
first announced	September 25, 2017 +
first launched	January 2018 +
full page name	intel/loihi +
instance of	neuromorphic chip +
ldate	January 2018 +
main image	+
manufacturer	Intel +
market segment	Artificial Intelligence +
max cpu count	16,384 +
name	Loihi +
neuron count	131,072 +
process	14 nm (0.014 μm, 1.4e-5 mm) +
smp max ways	16,384 +
synapse count	130,000,000 +
technology	CMOS +
transistor count	2,070,000,000 +