Coverage Across Multiple Power Domains: Theory Deep Dive

Foundational theory

Coverage Across Multiple Power Domains is core to Power State Verification. Treat each power behavior change as a correctness and signoff risk decision.

Core concepts explained

• Single-domain closure is insufficient once domains interact through shared clocks, buses, memory, and always-on control planes; coverage must capture cross-domain state combinations and transition interleavings that expose dependency bugs. Practical coverage models avoid combinational explosion by grouping states into risk classes (fully-on, retention, collapsed, transitional) and prioritizing high-impact intersections such as producer-off/consumer-on, shared-memory retention mismatches, and staggered wakeups across coherency participants. Each bin should tie to an observable correctness objective: no X-propagation into active logic, no stale data after restore, no orphaned transaction during domain collapse, and no interrupt loss across wake sequences. Signoff quality comes from merging simulation, emulation, and formal evidence into one closure view so unhit bins are triaged by silicon risk rather than waived on raw percentage pressure.

• Primary metric: Risk-weighted coverage closure for domain-state cross products, inter-domain transition pairs, and wakeup cause by mode combinations.

• Primary artifact: Multi-domain coverage plan with cross-product reduction rules, risk-ranked bins, and signoff waiver criteria.

• Owners: verification lead, SoC low-power architect, emulation and prototyping owner, formal coverage owner, program quality owner

• Power intent and RTL behavior must stay aligned through transitions

• Proof quality beats broad waive strategies in low-power closure

Why this matters in low-power signoff

Power-state verification is a protocol verification problem: legal transitions, ordering contracts, and corner-case concurrency. Teams that enforce this reduce false alarms and real escapes.

Mental model

POWER STATE TABLE

State     CORE   GPU   RET   ISO   VALID EXIT
--------  -----  ----  ----  ----  -----------------------------
ON        ON     ON    OFF   OFF   normal operation
IDLE      ON     CLK-G OFF   OFF   activity drops below threshold
SLEEP     OFF    OFF   ON    ON    wake_event && restore_done
GPU-NAP   ON     OFF   OFF   ON    gpu_irq || host_request
DEEP-SLP  OFF    OFF   ON    ON    aon_timer || external_wakeup

Transition checks:
ON -> SLEEP: save -> isolate -> gate clocks -> power off
SLEEP -> ON: power on -> wait stable -> restore -> de-isolate

Worked intuition

1. Classify symptom first: illegal transition, corruption, isolation break, retention drift, or X-prop ambiguity.

2. Pinpoint first phase boundary where expected low-power behavior diverges.

3. Quantify movement in Risk-weighted coverage closure for domain-state cross products, inter-domain transition pairs, and wakeup cause by mode combinations. before broad refactors.

4. Collect Multi-domain coverage plan with cross-product reduction rules, risk-ranked bins, and signoff waiver criteria. with fixed run metadata and mode sequencing.

5. Apply one bounded fix and replay both targeted and broader scenarios.

6. Publish owner-signed closure note with rollback trigger.

Common misconceptions

• Passing nominal ON/OFF smoke proves transition correctness.

• UPF compile clean means all intent semantics are correct.

• All X-prop failures indicate real product escapes.

• Retention behavior can be trusted without multi-cycle restore stress.

Low-power verification deep dive

Power-state correctness is a protocol contract: legal transitions, robust sequencing, and safe concurrent event handling.

Concept diagram

PST CONTROL LOOP

state request -> legality check -> handshake sequencing -> mode entry -> monitored exit

Metric graph

STATE RISK MIX

illegal transitions     ██████
sequence race bugs      █████
stable mode paths       ████████

Metrics and artifacts to collect

• PST legality matrix

• illegal transition histogram

• entry/exit handshake coverage

• mode sequencing anomaly log

Mini case study

A sporadic low-power failure closed only after proving a wake-versus-thermal race in PMU transition sequencing.

Debug branches

• Validate legal state graph first.

• Stress concurrent control events and asynchronous wakeups.

• Bind fixes to explicit transition and owner contracts.

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.

Theory reinforcement

Theory matters when it predicts concrete failure signatures and closure boundaries.

Translate LPV semantics into reproducible verification outcomes.