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456 lines
18 KiB
Text
456 lines
18 KiB
Text
-- FAMM-Neuromorphic Kernel Layer
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--
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-- Integrates FAMM (Frustrated Antiferromagnetic Manifold) for spatial mapping
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-- with neuromorphic event-driven processing.
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--
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-- This gives the kernel "spatial cognition" - it maps its environment
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-- (hardware topology, network geometry, thermal gradients) as a frustrated manifold
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-- and processes events using brain-inspired neural dynamics.
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--
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-- Key insight: Kernel becomes a *cognitive* entity, not just a resource manager.
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-- It "feels" its environment through FAMM frustration fields and responds via
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-- neuromorphic spike timing.
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--
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-- Truth Seal: [ SSS-ENE-FAMM-NEURO-2026-05-03 ]
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module FAMMNeuromorphicKernel where
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import BaseTypes
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import Memory
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import SyscallInterface
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import FAMM.Core
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import Neuromorphic.Core
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §1 FAMM Spatial Manifold — Kernel's "Cognitive Map"
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- FAMM (Frustrated Antiferromagnetic Manifold) represents the kernel's
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understanding of its environment as a geometric object.
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Each hardware component (CPU, memory, NIC, disk) is a "site" on the manifold.
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Interactions between components create "frustration" — geometric tension
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that the kernel can *feel* and respond to.
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This is based on: 2-Search-Space/FAMM/FAMM.lean
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-/]
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structure FAMMKernelMap where
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sites : Array Site -- Hardware components (CPU cores, NIC, etc.)
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bonds : Array Bond -- Interactions between components
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frustration : Q16_16 -- Current geometric frustration
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topology : ManifoldTopology -- S³, T³, or hyperbolic
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embeddingDim : Nat -- Dimension of ambient space
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structure Site where
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id : SiteID
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siteType : SiteType -- CPU, Memory, Network, Storage, Thermal
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coordinates : Vec3 Q16_16 -- Position in embedding space
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spin : Spin -- "Orientation" of resource
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energy : Q16_16 -- Current load/thermal energy
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inductive SiteType where
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| CPUCore -- Computational resource
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| MemoryNode -- RAM/cache hierarchy
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| NetworkIF -- NIC, virtual interfaces
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| StorageIO -- Disk, SSD
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| ThermalZone -- Temperature sensor region
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| PowerDomain -- PSU / voltage regulator
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| SyscallPortal -- Linux shim interface
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structure Bond where
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source : SiteID
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target : SiteID
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coupling : Q0_16 -- Interaction strength
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bondType : BondType
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inductive BondType where
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| DataFlow -- Memory traffic
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| ControlFlow -- Scheduling dependencies
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| ThermalLink -- Heat diffusion
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| PowerRail -- Electrical coupling
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| NetworkPath -- Latency topology
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| Frustration -- Competing demands
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §2 Neuromorphic Event Layer — Kernel's "Nervous System"
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Neuromorphic processing: event-driven, spike-based computation.
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Instead of polling (wasteful), the kernel responds to *spikes* —
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discrete events that carry information via timing.
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Inspired by: biological neural networks, TrueNorth, Loihi.
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But implemented purely in GCL with formal semantics.
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-/]
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structure NeuromorphicLayer where
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neurons : Array Neuron
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synapses : Array Synapse
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spikeQueue : Queue Spike
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time : Timestamp -- Global neuromorphic time
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dt : Microseconds -- Simulation timestep
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structure Neuron where
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id : NeuronID
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site : SiteID -- Maps to FAMM site
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potential : Q16_16 -- Membrane potential
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threshold : Q16_16 -- Firing threshold
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refractory : Microseconds -- Post-spike recovery time
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lastSpike : Timestamp
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neuronType : NeuronType
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inductive NeuronType where
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| Sensor -- Detects hardware events (interrupts, timers)
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| Interneuron -- Processes within kernel
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| Motor -- Triggers actions (syscalls, scheduling)
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| Memory -- Stores temporal patterns
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| Attention -- Focuses processing on salient regions
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structure Synapse where
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pre : NeuronID
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post : NeuronID
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weight : Q0_16 -- Synaptic strength
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delay : Microseconds -- Axonal delay
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plasticity : PlasticityRule -- Learning rule
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inductive PlasticityRule where
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| STDP -- Spike-Timing Dependent Plasticity
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| Hebbian -- Fire together, wire together
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| Homeostatic -- Maintain target activity
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| LawfulBound -- Constrained by BindResult cost
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structure Spike where
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neuron : NeuronID
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time : Timestamp
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amplitude : Q16_16 -- Information content
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witness : String -- What caused this spike?
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §3 FAMM-Neuromorphic Integration — "Feeling" the Kernel
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- The core integration: FAMM geometry drives neuromorphic dynamics.
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High frustration in FAMM → high activity in nearby neurons.
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Geometric curvature → spike timing patterns.
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The kernel literally "feels" its environment and responds.
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-/]
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def updateFAMMFromHardware : IO Unit := do
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-- Sample hardware state
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let cpuLoad ← syscall Syscall.ReadCPULoad
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let memPressure ← syscall Syscall.ReadMemoryPressure
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let netLatency ← syscall Syscall.ReadNetworkLatency
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let temperature ← syscall Syscall.ReadThermalZones
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-- Update FAMM site energies
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for site in fammMap.sites do
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match site.siteType with
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| .CPUCore =>
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site.energy := cpuLoad[site.id]!
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| .MemoryNode =>
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site.energy := memPressure
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| .NetworkIF =>
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site.energy := netLatency
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| .ThermalZone =>
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site.energy := temperature[site.id]!
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| _ => pure ()
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-- Recalculate frustration field
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fammMap.frustration := computeFrustration fammMap
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-- Generate neuromorphic spikes from frustration changes
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for site in fammMap.sites do
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let deltaFrustration := site.energy - site.previousEnergy
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if abs deltaFrustration > SENSOR_THRESHOLD then
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emitSpike {
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neuron := siteToNeuron site.id
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time := now ()
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amplitude := deltaFrustration
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witness := "FAMM_frustration_" ++ site.id.toString
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}
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def computeFrustration (map : FAMMKernelMap) : Q16_16 := do
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-- FAMM frustration: sum over bonds of |J_ij * S_i * S_j|
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-- where J_ij is coupling, S_i is site spin
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let total := map.bonds.foldl (\acc bond =>
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let s_i := map.sites.find! bond.source
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let s_j := map.sites.find! bond.target
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let contribution := bond.coupling * s_i.spin * s_j.spin
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acc + abs contribution
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) 0
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total
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §4 Event-Driven Kernel Main Loop
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Main loop: event-driven, not polling.
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Instead of:
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while true:
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check all hardware
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schedule processes
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sleep(1ms)
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We do:
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waitForSpike()
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processSpike(spike)
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propagateThroughSynapses()
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Massive efficiency gain: kernel only "thinks" when something happens.
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-/]
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def neuromorphicMainLoop : IO Unit := do
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forever $ do
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-- Wait for next event (spike or syscall)
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event ← waitForEvent
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match event with
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| .Spike spike =>
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-- Update FAMM based on spike origin
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updateFAMMFromSpike spike
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-- Propagate through neuromorphic network
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propagateSpike spike
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-- Check if motor neurons fire → take action
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checkMotorNeurons
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| .Syscall syscall =>
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-- Syscalls generate spikes in sensor neurons
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let sensorSpike := syscallToSpike syscall
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injectSpike sensorSpike
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-- Continue neuromorphic processing
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propagateSpike sensorSpike
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| .Timer tick =>
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-- Periodic update of FAMM manifold
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updateFAMMFromHardware
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-- Decay neuron potentials (leakage)
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decayNeurons tick.dt
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def propagateSpike (spike : Spike) : IO Unit := do
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let neuron ← findNeuron spike.neuron
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-- Update postsynaptic neurons
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for synapse in neuron.outgoingSynapses do
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let target ← findNeuron synapse.post
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-- STDP: timing matters
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let timeDiff := spike.time - target.lastSpike
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let weightUpdate := stdpUpdate synapse.plasticity timeDiff
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synapse.weight := clamp (synapse.weight + weightUpdate) 0 1
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-- Add to postsynaptic potential
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target.potential := target.potential +
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(spike.amplitude * synapse.weight)
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-- Check for spike generation
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if target.potential > target.threshold &&
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(now () - target.lastSpike) > target.refractory then
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let newSpike := {
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neuron := target.id
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time := now ()
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amplitude := target.potential
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witness := "propagated_from_" ++ spike.neuron.toString
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}
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queueSpike newSpike
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target.potential := 0 -- Reset after spike
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target.lastSpike := now ()
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §5 Motor Actions — Kernel "Decisions"
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Motor neurons trigger actual kernel actions.
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This is where neuromorphic processing translates to system calls.
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-/]
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def checkMotorNeurons : IO Unit := do
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for neuron in neuromorphicLayer.neurons do
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if neuron.neuronType == .Motor && neuronHasSpiked neuron then
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executeMotorAction neuron
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def executeMotorAction (neuron : Neuron) : IO Unit := do
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match neuron.motorFunction with
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| .ScheduleProcess pid =>
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-- Context switch triggered by neural activity
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syscall $ Syscall.Schedule pid
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| .AllocateMemory size =>
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-- Memory allocation triggered by "need"
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let ptr ← syscall $ Syscall.MemoryAllocate size
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recordAllocation ptr size neuron.id
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| .SendPacket dst data =>
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-- Network transmission
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syscall $ Syscall.NetworkSend dst data
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| .TriggerBindLoss req =>
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-- Lawful loss computation triggered by manifold frustration
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let result ← lawfulLossHandleRequest req
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if !result.lawful then
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-- High frustration → spawn Warden for validation
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spawnWardenValidation result
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| .Sleep duration =>
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-- Intentional idle when system "calm"
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syscall $ Syscall.Sleep duration
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §6 Attention and Salience — Kernel "Focus"
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Attention mechanism: kernel focuses processing on salient regions.
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High frustration areas of FAMM get more neural resources.
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This is like a "spotlight" of cognitive attention.
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-/]
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def updateAttention : IO Unit := do
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-- Find regions of high frustration in FAMM
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let salientSites := fammMap.sites.filter (\s => s.energy > ATTENTION_THRESHOLD)
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-- Allocate more neurons to processing these regions
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for site in salientSites do
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let attentionNeuron ← findOrCreateAttentionNeuron site.id
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attentionNeuron.gain := 2.0 -- Amplify signals
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-- Reduce resources for calm regions
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let calmSites := fammMap.sites.filter (\s => s.energy < CALM_THRESHOLD)
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for site in calmSites do
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let attentionNeuron ← findAttentionNeuron site.id
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attentionNeuron.gain := 0.5 -- Attenuate signals
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §7 Learning and Adaptation — Kernel "Memory"
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- The kernel learns from experience via synaptic plasticity.
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Repeated patterns of activity strengthen relevant synapses.
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This is "muscle memory" for the operating system.
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-/]
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def kernelLearningStep : IO Unit := do
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-- STDP: strengthen synapses where pre→post timing is causal
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for synapse in neuromorphicLayer.synapses do
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let preNeuron ← findNeuron synapse.pre
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let postNeuron ← findNeuron synapse.post
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if preNeuron.lastSpike < postNeuron.lastSpike then
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-- Pre caused post: strengthen
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let delta := LEARNING_RATE * (1 - synapse.weight)
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synapse.weight := min 1.0 (synapse.weight + delta)
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else if preNeuron.lastSpike > postNeuron.lastSpike then
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-- Post preceded pre: weaken (anti-causal)
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let delta := LEARNING_RATE * synapse.weight
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synapse.weight := max 0.0 (synapse.weight - delta)
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-- Homeostasis: maintain target firing rates
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for neuron in neuromorphicLayer.neurons do
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let recentSpikes := countSpikes neuron (now () - 1000000) -- Last second
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if recentSpikes > TARGET_RATE then
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-- Too active: increase threshold
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neuron.threshold := neuron.threshold * 1.1
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else if recentSpikes < TARGET_RATE then
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-- Too quiet: decrease threshold
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neuron.threshold := neuron.threshold * 0.9
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §8 Integration with LawfulLoss — "Feeling" Legally
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-- ═══════════════════════════════════════════════════════════════════════════
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/-- Every kernel action produces a BindResult witness.
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The kernel is *aware* of the cost of its own operations.
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This connects to: Semantics.LawfulLoss.lawfulLoss
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-/]
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def actionWithWitness (action : KernelAction) : IO BindResult := do
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let before ← sampleFAMMState
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-- Execute action
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executeAction action
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let after ← sampleFAMMState
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-- Compute lawful loss
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let invariantsPreserved := checkInvariants before after
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let cost := computeFrustrationDelta before after
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let witness := generateWitness action before after
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let result := lawfulLoss invariantsPreserved cost witness .control
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-- Log for verification
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recordBindResult result
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return result
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-- ═══════════════════════════════════════════════════════════════════════════
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-- §9 Boot Initialization
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-- ═══════════════════════════════════════════════════════════════════════════
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def initFAMMNeuromorphic : IO Unit := do
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consoleLog "[FAMM-NEURO] Initializing spatial cognition..."
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-- Discover hardware topology
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let cpuCores ← syscall Syscall.EnumerateCPUs
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let memoryBanks ← syscall Syscall.EnumerateMemory
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let networkInterfaces ← syscall Syscall.EnumerateNetwork
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let thermalZones ← syscall Syscall.EnumerateThermal
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-- Create FAMM sites for each hardware component
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for cpu in cpuCores do
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fammMap.sites.push {
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id := mkSiteID "cpu_" ++ cpu.id
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siteType := .CPUCore
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coordinates := cpu.physicalLocation -- NUMA topology
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spin := Spin.up
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energy := 0
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}
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for mem in memoryBanks do
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fammMap.sites.push {
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id := mkSiteID "mem_" ++ mem.id
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siteType := .MemoryNode
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coordinates := mem.physicalLocation
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spin := Spin.down -- Antiferromagnetic coupling with CPU
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energy := 0
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}
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-- Create bonds based on physical topology
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createTopologyBonds fammMap
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-- Initialize neuromorphic network
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for site in fammMap.sites do
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-- Each site gets a sensor neuron
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let sensorNeuron := createNeuron {
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site := site.id
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neuronType := .Sensor
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potential := 0
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threshold := SENSOR_THRESHOLD
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}
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-- Connect sensors to interneurons
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let interNeuron := createNeuron {
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neuronType := .Interneuron
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threshold := INTERNEURON_THRESHOLD
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}
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createSynapse sensorNeuron.id interNeuron.id {
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weight := 0.5
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delay := 100 -- 100 microseconds
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plasticity := .STDP
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}
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consoleLog $ "[FAMM-NEURO] Map initialized: " ++
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fammMap.sites.size.toString ++ " sites, " ++
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neuromorphicLayer.neurons.size.toString ++ " neurons"
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end FAMMNeuromorphicKernel
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