A block encounters a Handoff to Foundry Operations issue during late implementation.
Metric fails at review meeting
Engineer captures report and layout snapshot
Root cause traced to incorrect assumption from prior stage
Minimal fix applied and documented
Signoff matrix re-run on tagged database
Closure restored with documented risk and regression proof.
After solving the example, write the debrief a lead would expect: what changed, why it worked, what could regress, and what permanent methodology update prevents recurrence.
STAFF REVIEW MEMO — Signoff and Tapeout / Handoff to Foundry Operations
1. Current state
- Failing / watched metric: Foundry submission manifest with verification stamps
- Database tag, corner/mode, tool version: <fill before review>
- Physical scope: block, hierarchy, macro region, clock domain, or net class
2. Root-cause hypothesis
- Most likely mechanism: <name physical or constraint mechanism>
- Competing hypothesis: <name the second plausible cause>
- Evidence still missing: <report/map/schematic/check>
3. Proposed action
- Minimal reversible fix: <physical, constraint, ECO, or methodology change>
- Expected improvement: <metric delta>
- Regression risk: late-stage schedule slip, silicon risk, or cross-stage regression
4. Regression and signoff
- Re-run: Foundry submission manifest with verification stamps
- Must not regress: Mask prep and manufacturing kickoff.
- Decision owner: PD ownerTapeout is an auditable decision backed by tagged artifacts.
closure dashboard: timing, power, PV, DFT, package, and open waivers
revision manifest: RTL, netlist, SDC, GDS/OASIS, library, rule deck
waiver register: rule, count, owner, approver, expiration
foundry handoff package checklist
Timing and power are green, but the GDS tag differs from the STA database tag. The design is not ready. Reconcile the manifest and rerun signoff on the exact export database.
If a metric is yellow, name the owner, date, and mitigation before signoff review.
If the tag is mismatched, stop export; traceability is a hard gate.
If post-mask ECO is requested, confirm allowed metal layers before promising a fix.
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>Tapeout is an auditable decision backed by tagged artifacts. 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.