Supply Network Modeling

What this topic teaches

Supply Network Modeling converts LPV concepts into staff-level verification decisions. Model supply nets and supply sets with enough fidelity to reflect real domain dependencies, including shared rails, switched rails, always-on islands, and hierarchical inheritance from top-level supplies into subdomains. Exercise nominal, brownout-like, and transition windows to reveal sequencing bugs that only appear when parent-child supplies move asynchronously. The simulation model should explicitly capture control-to-rail timing assumptions (switch enable, acknowledgment, settle latency) so protocol checks can distinguish valid delay from genuine power-control deadlock or early functional access.

Senior-engineer framing question

When illegal transition rate, corruption incidence, and deterministic replay quality under low-power scenarios regresses, can you isolate first failing low-power boundary, prove it with artifacts, assign owners, and close with rollback-safe validation?

LOW-POWER VERIFICATION FLOW - Supply Network Modeling

power intent and mode definitions
      |
      v
domain controls and transition sequencing
      |
      v
simulation behavior (isolation, retention, corruption)
      |
      v
assertions and coverage evidence
      |
      v
triage, bounded fix, and signoff closure

Evidence to collect

• Primary metric: illegal transition rate, corruption incidence, and deterministic replay quality under low-power scenarios.

• Primary artifact: evidence packet for Supply Network Modeling: transition timeline, assertions, and before-after replay summary.

• Owners to include: LPV lead, power-intent owner, Power-Aware Simulation owner.

• One reproducible failing scenario and one stable comparator run.

• One fixed metadata run with branch and configuration tags locked.

Ownership layers

OWNERSHIP LAYERS - Supply Network Modeling

+----------------------+--------------------------------+--------------------------------+
| Team                 | Primary responsibility         | Closure artifact               |
+----------------------+--------------------------------+--------------------------------+
| LPV lead | scenario intent and closure      | review rationale memo          |
| power-intent owner | transition and boundary contract | timeline + assertion packet    |
| Power-Aware Simulation owner | regression signoff readiness     | validation matrix + risk note  |
+----------------------+--------------------------------+--------------------------------+

Decision matrix

EVIDENCE MATRIX - Supply Network Modeling

+-----------------------------+--------------------------------+--------------------------------+---------------------------+
| Evidence                    | Tells you                      | Does not prove                 | Next action               |
+-----------------------------+--------------------------------+--------------------------------+---------------------------+
| transition timeline traces  | first failing LP phase         | complete root-cause ownership  | correlate with intent map |
| UPF-aware assertion logs    | contract violations by phase   | silicon product impact         | map to scenario severity  |
| corruption/X classification | actionable vs noisy failures   | legal transition completeness  | replay key mode corners   |
| save/restore snapshots      | state integrity movement       | isolation correctness          | pair with crossing checks |
| before-after regressions    | mitigation movement quality    | long-tail stability            | run full matrix           |
+-----------------------------+--------------------------------+--------------------------------+---------------------------+

Key takeaways

• Start with transition-boundary classification before broad methodology changes.

• Tie each LPV claim to one proving artifact and one owner action.

• Close with validation matrix and rollback trigger for signoff safety.

Common pitfalls

• Waiving failures before first-failure boundary classification.

• Changing intent, RTL, and checkers in one step and losing causality.

• Declaring closure on local runs without broader replay coverage.

Low-power verification deep dive

Power-aware simulation quality is measured by realistic transition behavior and actionable failure classification.

Concept diagram

POWER-AWARE SIM FLOW

UPF + RTL + testbench -> elaboration -> transition simulation -> assertions and triage

Metric graph

SIM QUALITY SIGNALS

false-fail noise      █████
actionable failures   ███████
deterministic replay  ████████

Metrics and artifacts to collect

• elaboration semantic report

• power-aware run reproducibility matrix

• corruption and clamp behavior summary

• assertion signal-to-noise trend

Mini case study

A noisy regression became actionable after bucketing failures by transition phase and boundary type before fixing checks.

Debug branches

• Start from first failing phase, not final mismatch.

• Check semantic setup consistency before declaring design bug.

• Use one reproducible scenario per hypothesis branch.

Senior review question

Ask: what exact low-power transition boundary failed first, and which artifact proves the closure claim reproducibly?

Key takeaways

• Tie each LPV claim to a concrete transition boundary and one proving artifact.

• Prefer minimal reversible fixes with explicit owner and rollback criteria.

Common pitfalls

• Treating power-aware failures as random before boundary classification.

• Waiving X-prop failures before proving impact and root cause.

• Declaring closure without deterministic replay across key modes.