Coherence Fabric Debug: Inputs & Outputs

Inputs and outputs contract

Inputs & Outputs for Coherence Fabric Debug focuses on deadlock signature, ordering violation count, coherency timeout rate. The goal is to connect the observable symptom to protocol mechanism, ownership, and regression risk.

Treat these as a signed interface contract. Ambiguity here is the single biggest source of wasted integration weeks, because two teams debug against different assumptions.

INPUTS
  - protocol spec revision and feature subset
  - clock/reset assumptions
  - address map, ID/tag width, ordering attributes
  - traffic class, QoS, firmware register settings

OUTPUTS
  - legal transaction trace
  - integration waiver list
  - VIP/compliance report
  - owner-signed debug or signoff note

Transaction sequence

SEQUENCE — Coherence Fabric Debug

  initiator            interconnect/PHY            target
      |  request (id) ------->  |                     |
      |                         |  forward ----------> |
      |                         |                     | work
      |                         |  <---- response ---- |
      |  <----- complete ------ |                     |
      |
   metric captured here: deadlock signature, ordering violation count, coherency timeout rate

Ownership map

OWNERSHIP MAP — Coherence Fabric Debug

evidence type        owner who reads it
-----------------    ---------------------------
waveform/RTL        debug lead
spec/VIP            VIP owner
firmware/system     architecture owner

Rule: every metric must have a named owner before a review starts.

Protocol deep dive

Coherence extends memory transactions with snoop and state — traffic multiplies when software shares cache lines.

Concept diagram

COHERENCE TRAFFIC FLOW

RN issues coherent read
   -> HN looks up directory
   -> snoops to sharers
   -> data + state update returned

False sharing: different variables, same cache line -> coherence storm.

Metric graph

COHERENCY TRAFFIC STACK

data fetch        ████████
snoop responses   ██████████████
writebacks        ██████
maintenance ops   ████

High snoop stack with good IPC -> suspect line sharing before faster NoC.

Metrics and artifacts to collect

• snoop rate

• intervention latency

• coherency transaction mix

• false sharing indicators

Mini case study

Benchmark IPC looked fine but system power spiked: per-core counters were on one cache line. Padding counters fixed coherency traffic without any NoC change.

Debug branches

• If snoop latency high, check home node placement and directory policy.

• If ordering bug, run litmus sequences before microarch changes.

• If traffic storm, profile cache line sharing in software layout.

Senior review question

Ask: what is the first transaction that deviates, and which spec rule does it test?

Key takeaways

• Connect every protocol claim to a transaction identity and measurable metric.

• Store the artifact (waveform, log, counter) next to every signoff decision.

Common pitfalls

• Debugging timeouts without finding the first bad transaction.

• Quoting peak bus width without payload efficiency and retry overhead.

• Treating VIP compliance as a substitute for system integration replay.

Principal review addendum

Re-read Coherence Fabric Debug against one concrete product workload, not a synthetic directed test.

debug requires correlating transaction IDs, cache-line addresses, state transitions, and fabric backpressure.