Link Training: Review Checklist

Review checklist

Review Checklist for Link Training focuses on training pass rate, time-to-L0, fallback mode frequency. The goal is to connect observed symptom to boundary mechanism, ownership, and signoff risk.

• Boundary assumptions are versioned and signed.

• Mode matrix (power/clock/reset/stress) is explicit.

• Physical context (floorplan/package/power) is included where relevant.

• Metric and artifact references are reproducible.

• Waivers have owner, expiry, and mitigation.

• Owners signed: firmware owner, PHY owner, system validation lead.

Sign-off ownership

OWNERSHIP MAP — Link Training

artifact                  owner
----------------------    -----------------------------
integration artifact    firmware owner
implementation artifact PHY owner
signoff artifact        system validation lead

Every boundary issue needs a named owner before fixes start.

AMS deep dive

SerDes closure requires protocol, training, and SI evidence together.

Concept diagram

SERDES FLOW

training -> equalization -> lane margin -> protocol stability

Metric graph

BER VS EQ

BER
 ^
 |  high  low  high
 +-----------------> EQ setting

Reports and artifacts

• lane BER

• training state transitions

• EQ sweep report

• link retry counters

Mini case study

Link looked protocol-clean but lane margin collapsed under thermal sweep.

Debug branches

• Correlate LTSSM and lane metrics

• Check SI margins

• Review firmware timeout assumptions

Senior review question

Ask: what boundary condition proves this topic is actually closed?

Key takeaways

• State boundary, mode, and evidence tag with every claim.

• Always align analog, digital, and physical owners before signoff decisions.

Common pitfalls

• Fixing averages while tails still fail.

• Skipping package/supply evidence in jitter or SerDes issues.

• Shipping with waivers that lack owner and expiration criteria.

Principal AMS review addendum

Training protocols establish lane polarity, timing, equalization, and protocol states; digital state machines must synchronize with PHY indications and timeout policies.

Metric: training pass rate, time-to-L0, fallback mode frequency