Incremental Compile: Silicon PPA Impact

Silicon PPA and closure impact

Late-stage ECO quality directly impacts signoff confidence.

Area drivers

• Buffer growth

• Cell mix shifts

• Retiming duplication

Power drivers

• Leakage from LVT

• Clock power from gating/skew choices

Timing impact

• Critical path depth changes

• Hold/setup coupling

PD consequences

• Congestion ripple

• Handoff predictability

Verification burden

• Equivalence burden

• Regression matrix depth

PPA SNAPSHOT — Incremental Compile
area / dynamic / leakage / WNS / runtime

PPA takeaways

• QoR wins must survive signoff checks

• Correlation beats one-off gains

QoR snapshot

BEFORE / AFTER QOR — Incremental Compile

QoR score
  0 |                     --- target zone
 -1 |        ● regression
 -2 |             ● baseline
 -0.5|                  ● after fix
    +----------------------------------> iteration

Validate timing + area + power, not one number.

Synthesis deep dive

Incremental and ECO synthesis protect schedule only with strict regression discipline.

Concept diagram

INCREMENTAL ECO LOOP

identify delta -> localized compile -> patch -> regression -> release

Metric graph

ECO CYCLE TIME

full compile      ███████████
incremental       █████

Reports and artifacts

• incremental reuse

• ECO patch list

• LEC status

• regression matrix

Mini case study

Localized compile cut turnaround 40%, but skipped LEC caused rollback.

Debug branches

• Reuse ratio is not enough

• Patch locality check

• Always include equivalence hooks

Senior review question

Ask: what evidence proves this QoR move is real and stable?

Key takeaways

• State exact run context (RTL, SDC, libs, switches) with every QoR claim.

• Re-run timing, area, and power regressions after each synthesis ECO.

Common pitfalls

• Comparing runs with mismatched constraints or library views.

• Timing-only fixes that violate power or area budgets.

• Skipping equivalence checks after structural changes.

Principal synthesis review addendum

Incremental compile reuses stable optimization regions while targeting changed cones, reducing churn and iteration cost.

Metric: reuse ratio, localized QoR delta, compile turnaround time