How Setup/Hold Closure Playbook affects closure in Timing Closure.
Setup and hold have different corners, but fixes share physical context
Cell-delay-dominant and net-delay-dominant paths need different remedies
Cluster-first closure beats single-path whack-a-mole
1. Identify where Setup/Hold Closure Playbook sits in the PD flow
2. Name inputs consumed and outputs produced
3. State the metric that proves success or failure
4. Link to the next downstream stage that depends on this stepNarrate Setup/Hold Closure Playbook using metrics, not tool commands alone.
A senior engineer does not describe Setup/Hold Closure Playbook as a tool step. They explain what physical assumption changed, which report becomes trustworthy after that change, and which downstream owner can now make a decision.
Which stage of the database is valid: pre-CTS, post-CTS, post-route, post-fill, or final signoff.
Which approximation is still present: estimated RC, ideal clock, abstracted macro, vectorless power, or waived PV rule.
Which downstream result depends on this mechanism: ECO timing fixes.
You can point to report_timing (worst path clusters) + WNS/TNS trend before proposing a fix.
You can separate a local symptom from a systematic methodology issue.
You can explain why the fix is reversible, bounded, and cheaper than the alternatives.
Timing closure is a signoff matrix problem, not a single worst-path problem.
report_timing -max and -min with corner, mode, SI, and OCV enabled
path group WNS/TNS: which clock domain is actually blocking signoff
net delay percentage vs cell delay percentage
exception audit: false paths, multicycle paths, generated clocks
A -90 ps setup path has 75% net delay and crosses a macro channel. Sizing the launch flop is weak. The stronger response is to layer-promote or shorten the route, then re-run hold at the fast corner.
If net delay dominates, look for physical fixes before cell sizing.
If cell delay dominates, consider VT swap, sizing, or RTL micro-architecture.
If only one mode fails, inspect mode-specific SDC overlays and case analysis.
Ask yourself: what single report line would prove this page's concept is either passing or failing?
You are expected to predict what your fix can break before running it.
You should recognize when the issue is methodology, not one block's implementation.
You should communicate risk in tapeout language: owner, evidence, impact, mitigation, and decision date.
Deep subpage pages in this course should be read like real closure review material. For a 10+ year PD engineer, the bar is not remembering terminology; it is making a release-quality decision under ambiguity.
Names the failing metric, corner/mode, database tag, and analysis switches before proposing a fix.
Separates data, constraint, physical, tool, and methodology root causes instead of treating all failures as optimization problems.
Chooses experiments by information gain and reversibility, not by habit.
States regression blast radius across timing, route, power, PV, DFT, package, and tapeout manifest.
Turns recurring failures into methodology guardrails, dashboards, or checklist items.
STAFF / PRINCIPAL CLOSURE NOTE
Context:
stage: <pre-CTS | post-CTS | post-route | post-fill | signoff>
tag: <database / netlist / SDC / library stack>
failing metric: <exact report line>
affected scope: <block / hierarchy / path group / power domain / region>
Hypotheses:
H1: <most likely physical or constraint mechanism>
H2: <competing explanation>
H3: <methodology or input-data issue>
Decision:
next experiment: <cheap check that can falsify H1>
fix candidate: <minimal reversible change>
rollback trigger: <metric that says the fix is wrong>
regression set: <timing / route / power / PV / DFT / package>
escalation owner: <team or reviewer>Timing closure is a signoff matrix problem, not a single worst-path problem. Explain not only the preferred fix, but what margin or schedule you are spending to get it.
What must RTL, synthesis, CAD, STA, DFT, package, IP, or foundry agree to before this decision is final?
Which artifact becomes the source of truth after the decision: report, waiver, manifest, ECO script, or methodology deck?
What is the cost of being wrong: one rerun, ECO churn, mask risk, performance loss, or silicon escape?
"The current blocker is <metric> in <corner/mode/stage>. The leading cause is <mechanism>. I recommend <fix> because it is bounded and reversible. The regression surface is <domains>. If it fails, we escalate to <owner> with <evidence>."Always connect the concept back to a measurable signoff artifact.
A fix is not complete until you can name the regression checks.
Optimizing by habit instead of reading the current report.
Forgetting that a local fix can regress timing, routing, power, or PV elsewhere.