Practice aloud for Floorplanning Expanded → Channel Planning and Feedthroughs. Use METRIC → HYPOTHESIS → FIX → REGRESSION.
[INT][PD][TOPIC]
Q: Why do channels fail after seeming clean at floorplan stage?
A:
Later phases add CTS/ECO/feedthrough traffic that was not budgeted, consuming reserved capacity unexpectedly.
FOLLOW-UP TRAP: Assuming initial local-net estimate is sufficient.[INT][PD][TOPIC]
Q: How do you prioritize channel relief actions?
A:
First reduce avoidable feedthrough load, then improve channel geometry, and finally adjust routing policy or floorplan boundaries.
FOLLOW-UP TRAP: Immediately enlarging die without traffic classification.[INT][PD][TOPIC]
Q: What metric best signals impending channel crisis?
A:
Declining spare-track percentage combined with rising feedthrough share over milestones.
FOLLOW-UP TRAP: Watching only worst-path timing.At senior/principal level, the interviewer is testing ownership judgment more than vocabulary. Answer Channel Planning and Feedthroughs through failure mode, evidence, tradeoff, and release decision.
[INT][PD][STAFF]
Q: You inherit a late-stage Channel Planning and Feedthroughs failure one week before release. What do you do in the first hour?
A:
Freeze the database tag, name the failing metric (Channel occupancy and feedthrough utilization report), confirm corner/mode/stage, cluster the issue, assign the first experiment, and publish a regression/owner plan before making broad tool changes.
FOLLOW-UP TRAP: Jumping directly to optimization knobs without preserving evidence.[INT][PD][STAFF]
Q: When would you stop trying to improve Channel Planning and Feedthroughs and escalate?
A:
Escalate when the remaining risk crosses ownership boundaries, consumes shared margin, changes signed-off assumptions, or threatens Global route and post-CTS ECO success are tightly coupled to channel discipline.. Bring exact report lines and options, not vague concern.
FOLLOW-UP TRAP: Escalating without data or continuing alone after a cross-team decision is needed.Floorplan quality is the earliest predictor of place-and-route pain.
floorplan summary: core area, macro area, std-cell utilization
macro/channel review: pin-facing sides, halos, routing channels
power plan preview: ring width, strap pitch, follow-pin connectivity
trial route congestion: overflow around macro corners and pin fields
A 2 MB SRAM cluster is placed with pins facing the die edge. Trial route shows red overflow along the north edge. A senior PD answer is to rotate or mirror the SRAM, open the channel, and re-run trial route before attempting timing optimization.
If congestion is local to macro corners, inspect pin sides and halo width before reducing global utilization.
If IR is weak at the core edge, widen the ring or add edge straps before adding random decaps.
If timing paths cross the whole block, review pin assignment and macro orientation before post-route ECO.
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>Floorplan quality is the earliest predictor of place-and-route pain. 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.