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SC-NEUROCORE — Module Integration Reference

Status: Integrated Date: 2026-04-16 Tests: 1,173 passing across 19 modules Languages: Python, Go, Rust, SystemVerilog Co-Authored-By: Arcane Sapience protoscience@anulum.li

Overview

This document catalogues all modules industrialized from the research sandbox and integrated into the production SC-NEUROCORE tree. Each module has been:

  1. Copied (not moved) into src/sc_neurocore/ and tests/
  2. Given clean module names (no phase prefixes)
  3. Verified with full regression from the new locations
  4. Documented with class/function inventories for downstream documentation

Module Registry

Safety & Certification

safety_cert — IEC 61508 / ISO 26262 Safety Certification

  • Source: src/sc_neurocore/safety_cert/safety_cert.py
  • Tests: tests/test_safety_cert/test_safety_cert.py — 81 tests
  • Key Classes:
  • SafetyRequirement — Individual safety requirement with SIL/ASIL level
  • RequirementTracer — Bidirectional traceability matrix
  • FMEDAAnalyzer — Failure Modes, Effects, and Diagnostic Analysis
  • SafetyManualGenerator — IEC 61508 / ISO 26262 documentation generator
  • FormalPropertyLink — Links requirements to SymbiYosys formal proofs
  • ReliabilityPredictor — FIT rate and MTTF calculation (MIL-HDBK-217F)
  • CertificationAuditor — Automated compliance auditing
  • RiskGraph — Risk assessment with consequence/exposure/controllability
  • SafetyIntegrityVerifier — Cross-module SIL verification
  • DependencyAnalyzer — Inter-module dependency tracking

fault_injection — Resilience Testing

  • Source: src/sc_neurocore/fault_injection/fault_injection.py
  • Tests: tests/test_fault_injection/test_fault_injection.py — 22 tests
  • Key Classes:
  • FaultInjector — Configurable bit-flip / stuck-at fault injector
  • FaultModel — Fault type definitions (SEU, MBU, stuck-at)
  • RadiationProfile — Space/terrestrial radiation models
  • ResilienceBenchmark — Automated resilience scoring

ASIC & Hardware

asic_flow — Multi-PDK ASIC Generation

  • Source: src/sc_neurocore/asic_flow/asic_flow.py
  • Tests: tests/test_asic_flow/test_asic_flow.py — 67 tests
  • Key Classes:
  • PDKConfig — Process Design Kit configuration (Sky130, GF12, TSMC)
  • FloorplanGenerator — Automated floorplanning
  • TimingAnalyzer — Static timing analysis
  • PowerEstimator — Dynamic/leakage power estimation
  • DesignRuleChecker — DRC violation detection
  • FormalPropertyLink — SymbiYosys integration

uvm_gen — UVM Testbench Generator

  • Source: src/sc_neurocore/uvm_gen/uvm_gen.py
  • Tests: tests/test_uvm_gen/test_uvm_gen.py — 72 tests
  • Key Classes:
  • UVMGenerator — Full UVM testbench emission
  • RTLModule — RTL module abstraction
  • StimulusConfig — Constrained-random stimulus
  • CoverageSpec — Functional coverage specification
  • ScoreboardConfig — Self-checking scoreboard

chiplet — Multi-Die Chiplet Generator

  • Source: src/sc_neurocore/chiplet/chiplet_gen.py
  • Tests: tests/test_chiplet/test_chiplet_gen.py — 94 tests
  • Key Classes:
  • ChipletGenerator — Die-level generation with UCIe/BoW links
  • InterconnectTopo — Die-to-die topology (mesh, ring, star)
  • ThermalModel — Per-die thermal estimation
  • YieldEstimator — Multi-die yield modelling

Physical Substrates

spintronic — Magnetic-Domain SC Mapper

  • Source: src/sc_neurocore/spintronic/spintronic_mapper.py
  • Tests: tests/test_spintronic/test_spintronic_mapper.py — 66 tests
  • Key Classes:
  • SpintronicMapper — Maps SC networks to MTJ arrays
  • MagneticDomainSim — Micromagnetic co-simulation bridge
  • SpinTorqueModel — STT/SOT write models
  • TMRCalculator — Tunnelling magnetoresistance estimation

memristor — Memristor Crossbar Mapper

  • Source: src/sc_neurocore/memristor/memristor_mapper.py
  • Tests: tests/test_memristor/test_memristor_mapper.py — 70 tests
  • Key Classes:
  • CrossbarArray — Memristive crossbar abstraction
  • ConductanceModel — Non-linear conductance model
  • AgingSimulator — Device degradation simulation
  • CrossbarEstimator — Power/area estimation

analog_bridge — Stochastic-to-Analog Bridge

  • Source: src/sc_neurocore/analog_bridge/analog_bridge.py
  • Tests: tests/test_analog_bridge/test_analog_bridge.py — 27 tests
  • Key Classes:
  • AnalogBridge — SC-to-analog conversion layer
  • DACModel — Digital-to-analog output model
  • ADCModel — Analog-to-digital input model

Exascale & Runtime

hypervisor — Neuromorphic Multi-Tenant Hypervisor

  • Source: src/sc_neurocore/hypervisor/hypervisor.py
  • Tests: tests/test_hypervisor/test_hypervisor.py — 78 tests
  • Key Classes:
  • Hypervisor — Multi-tenant SC workload manager
  • Tenant — Isolated workload with resource quotas
  • ResourceAllocator — FPGA tile / memory partitioning
  • PreemptionPolicy — Priority-based preemption
  • HealthMonitor — Watchdog and heartbeat monitoring

digital_twin/twinsync — Digital Twin Synchronization

  • Source: src/sc_neurocore/digital_twin/twinsync.py
  • Tests: tests/test_twinsync/test_twinsync.py — 72 tests
  • Key Classes:
  • TwinSession — Time-warp optimistic simulation
  • NullMessageOptimizer — Conservative sync lookahead
  • DeltaCheckpoint — Memory-efficient state diffs
  • ReplayVerifier — Deterministic replay verification
  • DriftAutoCorrector — Real-time drift compensation
  • CheckpointAuditChain — SHA-256 tamper-evident chain
  • TwinFederation — Multi-twin GVT coordination

Frontiers

evo_substrate — Self-Replicating Evolutionary Substrate

  • Source: src/sc_neurocore/evo_substrate/evo_substrate.py
  • Tests: tests/test_evo_substrate/test_evo_substrate.py — 91 tests
  • Key Classes:
  • Genome, TopologyGene, NeuronGene, PlasticityGene — Genetic encoding
  • MutationEngine — Point, structural, duplication, swap mutations
  • CrossoverEngine — Multi-point crossover
  • FitnessEvaluator — Multi-objective fitness
  • ReplicationEngine — Generation-level evolution loop
  • OrganismEmitter — NIR + Verilog organism emission
  • SafetyBounds — Mutation space constraints
  • TileDeploymentTracker — FPGA tile allocation
  • HallOfFame — Historical best tracking
  • IslandModel — Multi-deme with migration
  • NoveltyArchive — Behavioural novelty search
  • ExtinctionDetector — Stagnation-triggered mass extinction
  • CoevolutionArena — Predator-prey dynamics
  • FormalSafetyGuard — Pre-deployment validation
  • TournamentSelector — Configurable selection pressure
  • ParetoFront — NSGA-II style non-dominated front
  • AgeRegulator — Maximum lifespan enforcement
  • BloatPenalizer — Genome complexity regularization
  • CPPNGenome — Compositional Pattern Producing Networks
  • HWFitnessCollector — FPGA execution feedback
  • EvoStatisticsTracker — Per-generation analytics
  • ComplexityTracker — Open-ended complexity metric

meta_plasticity — Mutable Plasticity Rules

  • Source: src/sc_neurocore/meta_plasticity/meta_plasticity.py
  • Tests: tests/test_meta_plasticity/test_meta_plasticity.py — 72 tests
  • Key Classes:
  • MetaPlasticityEngine — Self-modifying learning rules
  • PlasticityRule — Parameterised STDP/triplet rules
  • RuleEvolver — Evolutionary plasticity rule search
  • ConsolidationScheduler — Memory consolidation timing

autonomous_learning — High-Performance Online Plasticity Engine

  • Source: crates/autonomous_learning/, src/sc_neurocore/_native/, src/sc_neurocore/accel/go/autonomous_learning/
  • Tests: tests/test_learning/ — 3 tests (Parity & Unit)
  • Key Classes:
  • RustPlasticityRule — FFI Python class mapping STDP/BCM/R-STDP to Rust backend
  • LearningBridgeAccel — Julia C-FFI wrapper
  • autonomous_learning.PlasticityRule (Go) — Go Cgo wrapper

bioware — Biological-Hardware Interface

  • Source: src/sc_neurocore/bioware/bioware.py
  • Tests: tests/test_bioware/test_bioware.py — 79 tests
  • Key Classes:
  • BiowareInterface — Wet-lab / in-silico bridge
  • OrganoidModel — Cerebral organoid abstraction
  • MEAAdapter — Multi-electrode array interface
  • SpikeProtocol — Biological spike encoding

federated — Federated SC Learning

  • Source: src/sc_neurocore/federated/federated_sc.py
  • Tests: tests/test_federated/test_federated_sc.py — 93 tests
  • Key Classes:
  • FederatedCoordinator — Privacy-preserving aggregation
  • SecureAggregator — Secure multi-party computation
  • DifferentialPrivacy — DP-SGD noise injection
  • ModelCompressor — Communication-efficient compression

bci_studio — BCI Closed-Loop Control

  • Source: src/sc_neurocore/bci_studio/bci_primitives.py, bci_studio.py
  • Tests: tests/test_bci/ — 32 tests
  • Key Classes:
  • BCIClosedLoopEngine — Real-time neural decoding
  • StimulusGenerator — Closed-loop stimulation
  • SafetyMonitor — Charge density limiter

Unification

explainability — SC Explainability Tools

  • Source: src/sc_neurocore/explainability/explainability.py
  • Tests: tests/test_explainability/test_explainability.py — 71 tests
  • Key Classes:
  • ExplainabilityEngine — Bitstream-level explanation generation
  • CausalAttributor — Causal attribution for SC decisions
  • FormalPropertyLink — Formal verification anchoring

neuro_symbolic — Predictive Coding Primitives

  • Source: src/sc_neurocore/neuro_symbolic/predictive_coding.py
  • Tests: tests/test_neuro_symbolic/test_predictive_coding.py — 34 tests
  • Key Classes:
  • PredictiveCodingLayer — Hierarchical prediction error
  • SymbolEncoder — Hyperdimensional symbol binding
  • VerifiableInference — Formally verifiable reasoning

stochastic_doctor — Bitstream Diagnostics

  • Source: src/sc_neurocore/stochastic_doctor/diagnostics.py
  • Tests: tests/test_stochastic_doctor/test_diagnostics.py — 16 tests
  • Key Classes:
  • BitstreamDoctor — Health diagnostics engine
  • CorrelationDetector — Inter-stream correlation analysis
  • BitstreamAuditReport — Full audit trail

model_zoo — Auto-Verilog Model Zoo

  • Source: src/sc_neurocore/model_zoo/model_zoo.py
  • Tests: tests/test_model_zoo/test_model_zoo.py — 37 tests
  • Key Classes:
  • PluginRegistry — Neuron model plugin system
  • VerilogGenerator — One-command Verilog emission
  • DocGenerator — Auto-documentation from plugins
  • LIFPlugin, IzhikevichPlugin, AdExPlugin, HodgkinHuxleyPlugin

Test Summary

Module Location Tests
safety_cert tests/test_safety_cert/ 81
asic_flow tests/test_asic_flow/ 67
fault_injection tests/test_fault_injection/ 22
uvm_gen tests/test_uvm_gen/ 72
hypervisor tests/test_hypervisor/ 78
twinsync tests/test_twinsync/ 72
spintronic tests/test_spintronic/ 66
chiplet tests/test_chiplet/ 94
memristor tests/test_memristor/ 70
analog_bridge tests/test_analog_bridge/ 27
bioware tests/test_bioware/ 79
meta_plasticity tests/test_meta_plasticity/ 72
evo_substrate tests/test_evo_substrate/ 91
federated tests/test_federated/ 93
bci_studio tests/test_bci/ 32
explainability tests/test_explainability/ 71
neuro_symbolic tests/test_neuro_symbolic/ 34
stochastic_doctor tests/test_stochastic_doctor/ 16
model_zoo tests/test_model_zoo/ 37
TOTAL 1,173

Running Tests

Bash
# Single module
python3 -m pytest tests/test_evo_substrate/ -q

# All integrated modules
python3 -m pytest tests/test_safety_cert tests/test_asic_flow tests/test_fault_injection \
  tests/test_uvm_gen tests/test_hypervisor tests/test_twinsync tests/test_spintronic \
  tests/test_chiplet tests/test_memristor tests/test_analog_bridge tests/test_bioware \
  tests/test_meta_plasticity tests/test_evo_substrate tests/test_federated tests/test_bci \
  tests/test_explainability tests/test_neuro_symbolic tests/test_stochastic_doctor \
  tests/test_model_zoo -q

Provenance

All modules were industrialized through a multi-pass gap analysis and hardening process. This document serves as the single source of truth for what was integrated, where it lives, and how it is tested.

Rust Crate Architecture

The Research Rust crates (tinysc_riscv, core_engine, autonomous_learning, neuro_symbolic) remain as standalone crates and are NOT merged into engine/. Rationale:

  1. engine/ is a single PyO3/maturin crate (sc_neurocore_engine) with cdylib + rlib output, custom build config, and bridge/ Python source path. Adding unrelated crates would break the maturin develop / pip install -e . workflow.
  2. The Research Rust crates are standalone research crates with no Python binding.
  3. When any of them matures to production, it should be added as a separate workspace member under a new top-level crates/ directory (not inside engine/).

Future Workspace Migration (when ready)

TOML
# SC-NEUROCORE/Cargo.toml (new workspace root)
[workspace]
members = [
    "engine",
    "crates/tinysc_riscv",
    "crates/neuro_symbolic",
]

This preserves the engine's build integrity while enabling shared dependency resolution.