Cache Coherency · All levels
ReadShared and ReadUnique Flows: Reports & Metrics
Reports & Metrics for ReadShared and ReadUnique Flows.
Reports and metrics
Reports & Metrics for ReadShared and ReadUnique Flows explains how to reason from coherency invariant to measurable engineering decision.
A useful report turns read completion latency by request class into a decision, not just a dashboard number.
Trend view
METRIC TREND — read completion latency by request class
risk or inefficiency
^
| target band
| ------------------------
| o after root-cause fix
| o isolated reproducer
| o baseline symptom
+--------------------------------------> review iteration
Attach every point to a concrete artifact:
- design revision
- traffic profile
- firmware tag
- measurement scriptSeparate mechanism failures from workload effects.
Store measurement setup next to every metric point.
Require one root-cause narrative per significant shift.
Cache coherency deep dive
Cache coherence is a correctness contract across caches, interconnect, and software ordering.
Concept diagram
requester -> coherence fabric -> owner or memory -> state updateMetric graph
traffic mix across request, snoop, response, dataMetrics and artifacts to collect
coherence latency
invalidation rate
retry rate
stale-read incidents
Mini case study
Anchor debug to first stale read and the exact line state transition.
Debug branches
Track ownership
Track ordering
Track evidence
Senior review question
Ask: what is the first line state transition that deviates, and which ordering rule does it break?
Key takeaways
Tie every coherency claim to one cache line, one transaction identity, and one measurable counter.
Keep proof artifacts from simulation and silicon replay aligned by address, state, and ordering event.
Common pitfalls
Chasing bandwidth regressions without checking false sharing and line bouncing first.
Assuming coherence correctness implies memory consistency correctness.
Declaring closure without litmus, stress, and post-silicon replay evidence.