Cross Coverage and Interaction Space: Reports and Metrics

Reports and metrics

Reports and Metrics for Cross Coverage and Interaction Space focuses on high-risk cross-bin hit rate and redundant cross elimination ratio. The purpose is to turn memory observations into mechanism-backed actions with explicit owners and release-safe validation.

Reports should explain why high-risk cross-bin hit rate and redundant cross elimination ratio moved, not simply that it moved. Require evidence that links the movement to command behavior, queue policy, PHY margin, or reliability controls.

Before/after trend

BEFORE / AFTER GRAPH - Cross Coverage and Interaction Space

metric quality
  ^
  |                       o target band
  |                o post-fix sweep
  |           o
  |      o baseline (failing)
  +----------------------------------------------> iteration
      evidence capture   fix applied   closure run

Use this view to prove improvement is causal, not accidental.

Evidence matrix

VIP EVIDENCE MATRIX - Cross Coverage and Interaction Space

+-------------------------------+--------------------------------+--------------------------------+---------------------------+
| Evidence                      | Tells you                      | Does not prove                 | Next action               |
+-------------------------------+--------------------------------+--------------------------------+---------------------------+
| checker hit/miss + ACT/PRE mix    | locality and row-state cost    | lane-level capture integrity   | inspect training margins  |
| queue age + class breakdown   | fairness and starvation risk   | command legality details       | parse command timeline    |
| spec clause legality + bus timeline | timing-window pressure         | root cause by itself           | correlate with traffic map|
| eye / Vref / skew snapshots   | PHY margin and drift behavior  | controller policy quality      | pair with schedule logs   |
| CE/UE + scrub telemetry       | reliability trajectory         | immediate perf bottleneck only | map to hotspot addresses  |
+-------------------------------+--------------------------------+--------------------------------+---------------------------+

• Track p50/p95/p99 latency and effective bandwidth together.

• Include command and queue context alongside high-level counters.

• Tag reports with firmware, timing profile, and thermal state.

• Call out contradictory evidence instead of hiding it.

VIP deep dive

Coverage planning, cross coverage, closure triage, and quality metrics that prove verification depth beyond pass/fail regressions.

Concept diagram

VIP SECTION - Functional Coverage Modeling

testcase -> agents -> checkers -> coverage -> evidence

Metric graph

checker noise vs real violations trend

Reports and artifacts

• checker hit report

• coverage closure sheet

• compliance trace matrix

• regression health snapshot

Mini case study

A profile drift caused false checker storms until configuration hashes were locked in CI.

Debug branches

• Reproduce with locked seed and profile

• Isolate checker vs scoreboard vs DUT paths

• Map failure to spec clause and owner

Senior review question

Ask: which latency, bandwidth, and reliability evidence proves this VIP topic is closed under real traffic?

Key takeaways

• Always tie controller and PHY counter shifts to application latency and throughput outcomes.

• Lock firmware timing profile, thermal condition, and DIMM state before comparing VIP captures.

Common pitfalls

• Chasing peak bandwidth while ignoring p99 latency and fairness tails.

• Changing timing guardbands without separating SI noise from scheduling issues.

• Declaring closure without reliability gates, fault injection, and regression replay.

VIP atlas notes

Cross Coverage and Interaction Space should be read as an end-to-end VIP behavior, not as a single block definition. Production compliance closure reflects interactions between agents, checkers, coverage, and customer evidence before tapeout or IP release claims.

Cross coverage captures interactions such as burst length × cache state × error recovery path. Without disciplined cross strategy, teams over-cover Cartesian products while missing correlated failures that only appear under combined conditions. VIP inefficiency is multiplicative: one weak checker enable, one hollow coverage bin, or one non-reproducible failure repeated across regressions can dominate signoff risk.