Physical Design · All levels
Data and Libraries
Technology and constraint collateral that defines legal geometry, timing behavior, and signoff context before floorplan and place-opt.
Section goal
Build repeatable handoff discipline so every implementation run uses the same technology, timing, and abstract views.
Mechanism to narrate
Treat collateral as code: version, diff, and release tags with every run.
A clean library stack removes most late-stage mystery violations.
If view consistency is weak, closure debug becomes non-deterministic.
Senior course bar for this section
Every topic should end with a signoff decision, not only concept recall.
Every fix should state expected metric movement and likely regression surface.
Every open assumption should have an owner, tag, and review date.
Every recurring issue should become a methodology guardrail or checklist item.
pdk-technology-files/ — PDK Technology Files
lef-def-foundations/ — LEF/DEF Foundations
liberty-corners/ — Liberty Corners
timing-views-and-ocv-tables/ — Timing Views and OCV Tables
macro-abstracts-and-ip-handoff/ — Macro Abstracts and IP Handoff
sdc-versioning-and-constraint-handoff/ — SDC Versioning and Constraint Handoff
Related topics
Key takeaways
Library consistency is a schedule multiplier.
Most timing noise is view mismatch, not optimization weakness.
Detailed section notes
Interview performance is structured closure thinking under time pressure.
Reports and artifacts to inspect
one-slide metric dashboard for the scenario
hypothesis list sorted by likelihood and cost
one report/map per experiment
regression list after the proposed fix
Mini case study
A strong answer to any scenario starts with the failing metric and signoff context. A weak answer starts with a tool command or random optimization knob.
Debug branches
If you are stuck, restate the metric and ask for corner/mode/stage.
If multiple failures exist, separate hard gates from tracked risks.
If pressured to waive, describe approval path and silicon risk.
Senior review question
Ask yourself: what single report line would prove this page's concept is either passing or failing?
What changes at 10+ years
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.
Principal-level review bar
Hub 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.
What excellent looks like
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.
Closure note template
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>Tradeoffs a senior engineer must discuss
Technical tradeoff
Interview performance is structured closure thinking under time pressure. Explain not only the preferred fix, but what margin or schedule you are spending to get it.
Cross-team tradeoff
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?
Leadership communication
"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>."Key takeaways
Always connect the concept back to a measurable signoff artifact.
A fix is not complete until you can name the regression checks.
Common pitfalls
Optimizing by habit instead of reading the current report.
Forgetting that a local fix can regress timing, routing, power, or PV elsewhere.