Working definition
Mixed-signal neuromorphic hardware uses analog or subthreshold circuits for selected neuron, synapse, or memory dynamics and digital logic for routing, configuration, or observation. Device mismatch and noise can be computational resources or error sources depending on the model; calibration, temperature, aging, and fabrication variation are therefore part of the algorithmic contract.
Mechanism
- Map model state to analog circuit variables.
- Exchange events through digital routing.
- Calibrate or learn around physical variability.
Measurements
- Energy per declared operation or event
- Model fidelity and mismatch
- Temperature and run-to-run stability
Reproducibility controls
- Version hardware, software, firmware, and analysis code.
- Declare dataset, preprocessing, random seeds, and measurement boundary.
- Report repeated runs, variation, exclusions, and failed trials.
Limits and failure modes
- Analog precision differs from numerical precision.
- Calibration overhead belongs in system cost.
Mathematical connection
Formal structure without substrate erasure
Device variation through task output
Propagate measured mismatch, noise, and drift into model and task uncertainty.
Inputs
- Device distributions
- Calibration model
- Task mapping
Outputs
- Output uncertainty
- Sensitivity ranking
- Calibration target
Limit: A probability model cannot recover unmeasured failure modes or justify excluding calibration and conversion costs.
Technical and governance sources
- [1]NeuroBench: Advancing Neuromorphic Computing Through Collaborative, Fair and Representative Benchmarking · National Institute of Standards and Technology
Establishes: A community framework separating algorithm and system tracks and defining task, correctness, efficiency, and reporting procedures intended to make neuromorphic results more comparable and reproducible.
Boundary: A benchmark ranks submitted systems on declared tasks and metrics. It does not prove general intelligence, biological equivalence, safety, usefulness outside the benchmark, or superiority under unreported host and data costs.
- [2]SpiNNaker2 Developer Portal and Hardware Documentation · SpiNNcloud Systems and SpiNNaker2 community
Establishes: Maintained technical documentation for a many-core, event-based neuromorphic platform, including chip topology, processing elements, communication, software interfaces, and supported computational workloads.
Boundary: Architecture documentation establishes available mechanisms, not universal speed, energy, learning, biological plausibility, or production readiness. Claims require a named board, software version, workload, and system boundary.