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Course contents

  • How to Use This Course
  • Reading Path
  • Cache Coherency Glossary
  • The Shared Course Model
  • Cache Coherency Revision Sheet
  • Why Coherence Exists8
  • States and Protocols12
  • Transactions12
  • Races and Controller Design8
  • Progress and the Fabric16
    • Virtual Networks and Progress
    • Filtering and Snoop Pruning
    • Latency, Fairness and QoS
    • Hierarchical and Chiplet Coherence
  • Ordering and Synchronization12
  • Performance and Scalability12
  • Real Protocols12
  • SoC Integration12
  • Power, Clocking and Reliability12
  • Verification12
  • Debug and Bring-up12
  • Interview and Design Review17
  • Capstone: A Coherent Model Lab5
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←Cache Coherency
  1. Topics
  2. Cache Coherency
  3. Progress and the Fabric

Part 5 of 14Part 5 of 14/Progress and the FabricAll levels

Progress and the Fabric

Connect coherence transactions to finite resources, conservative filtering, fair service and hierarchical paths.

  • 4topics
  • 16lessons

Topics in this section

  1. 1Virtual Networks and Progress4 lessons
    • A Protocol Deadlock
    • Message Classes and Virtual Networks
    • Deadlock, Livelock, Starvation
    • Stating Progress Assumptions
  2. 2Filtering and Snoop Pruning4 lessons
    • The Cost of Broadcast
    • Snoop Filter Correctness
    • Multicast and Ack Collection
    • Filter Eviction and Back-Invalidation
  3. 3Latency, Fairness and QoS4 lessons
    • Anatomy of a Miss Latency
    • Fairness on a Contended Line
    • QoS Classes and Coherence
    • Starvation Cases
  4. 4Hierarchical and Chiplet Coherence4 lessons
    • Two-Level Directories
    • Clusters and Global Homes
    • Coherence Across Dies
    • Hierarchy Trade-Offs

The earlier transactions established how permission and current data move. A fabric must also provide resources for those obligations to finish. Work from a concrete dependency cycle to filtered traffic, then latency, service policies and hierarchical responsibility.

Learning path moves from finite-resource dependencies to filtering, fairness and hierarchical data responsibility.
Safety obligations stay fixed while resource, traffic and topology choices change.

Sixteen lessons

Lesson

After it you can...

A Protocol Deadlock

Explain the reachable P/Q resource cycle and the request < forward < response rule that breaks it.

Message Classes and Virtual Networks

Tell protocol deadlock from routing deadlock and check that classes have independent resources.

Deadlock, Livelock, Starvation

Classify failure using enabled work and useful completion.

Stating Progress Assumptions

State assumptions A1-A6 behind a progress claim.

The Cost of Broadcast

Count probes and responses without pretending they are latency.

Snoop Filter Correctness

State the inclusive-filter invariant and where false positives come from.

Multicast and Ack Collection

Match responses to active obligations rather than raw packet counts.

Filter Eviction and Back-Invalidation

Free an entry only after clean holders ack or dirty data reaches memory.

Anatomy of a Miss Latency

Compute an illustrative critical path for a permission miss.

Fairness on a Contended Line

Define eligibility and the scope of round-robin selection.

QoS Classes and Coherence

Preserve protocol safety and completion capacity under priority.

Starvation Cases

Find unbounded bypass and reject unsupported cycle bounds.

Two-Level Directories

Distinguish global cluster coverage from local cache records.

Clusters and Global Homes

Explain how a cluster's local permissions are bounded by the global record, and count die-crossing legs.

Coherence Across Dies

Separate link acceptance, coherent completion and failure recovery.

Hierarchy Trade-Offs

Compare total scoped metadata and required paths under stated assumptions.

Suggested order: resources, filtering, service, then hierarchy. Keep the shared course model open. New finite-resource policies and cluster topology are explicitly introduced where used, rather than silently changing H's ordering or data rules.

A design can preserve every current value and still hang. It can also move packets continuously while one request starves. Safety, deadlock freedom, fairness and numerical latency bounds need different evidence.

Check yourself Why does reducing probe fanout not prove either fairness or deadlock freedom?

It changes the work sent, not necessarily the held/requested resource graph or selection policy. The remaining required data path can still deadlock or be bypassed.

Related topics

  • Shared course model

  • Prerequisite: controller resources

  • Start: resources and progress

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See also

  • How to Use This Course
  • Reading Path
  • Cache Coherency Glossary