Silicon-to-Design Correlation

Turn first-silicon measurements into
changes before the next tapeout.

Tapeout maps every measurement to its design, physical, test, and manufacturing context — then identifies which assumptions systematically failed to predict silicon.

Talk to usHow it works
The Problem

Silicon never matches the models. Finding out why takes weeks.

01

Fragmented identifiers

RTL modules, synthesized instances, physical coordinates, timing endpoints, scan chains, test numbers, monitor IDs, die coordinates — all disconnected across teams and tools.

02

Slow feedback

Post-silicon learnings take months to reach pre-silicon teams — if they arrive at all. The same margin errors resurface across tape-outs.

03

No correlation layer

STA predictions vs. actual silicon timing. DFT coverage vs. real defect escapes. Power models vs. measured power. Nobody bridges these systematically across vendors.

How It Works

Four steps from measurement to correction.

01

Capture

Ingest signoff, DFT, tester, and monitor data for each tapeout revision. STA reports, Liberty libraries, DEF/LEF, STDF, wafer maps, shmoo plots.

02

Map

Connect silicon measurements to the paths, cells, blocks, physical regions, and design assumptions that produced them. Build the identity graph across every naming system.

03

Explain

Quantify the gap between predicted and measured behavior. Rank the conditions responsible — cell family, Vt class, physical location, routing congestion, PVT corner, lot, wafer position.

04

Correct

Generate reviewed changes to margins, constraints, test content, and instrumentation before the next tapeout. Derates, guardbands, ECO candidates, monitor placement recommendations.

Why Now
2nm+
Advanced nodes make correlation exponentially harder — manual methods can’t keep up
18mo
Average tape-out cycle. Every respin adds 6–12 months and $50M+ in NRE
10–15%
Performance left on the table due to conservative guardbands teams can’t calibrate against real silicon
The Core

The silicon identity graph.

Every data source uses different identifiers. Tapeout builds a versioned graph that links them all — so you can navigate from a failing die back to the exact design assumptions that caused the failure.

test_4817
scan chain 72logic cone 14instances U1032, U1033region x=420–460, y=180–220CPU_CORE_3library rev. 17wafer W42
Output

Actionable corrections, not dashboards.

Tapeout produces specific, ranked recommendations that engineers can review and apply before the next tape-out.

Timing derates

Cell-family-specific derate adjustments backed by measured silicon margin.

Guardband corrections

Updated PVT assumptions derived from actual voltage, temperature, and process sensitivity.

Root-cause hypotheses

Ranked explanations: which variables explain the prediction-to-silicon gap.

ECO candidates

Paths and regions that need margin adjustment, power-grid investigation, or cell-class changes.

Test coverage gaps

New ATPG targets, observation-point recommendations, and monitor placement based on real escapes.

Spatial heat maps

Wafer-level and layout-level visualization of where predictions diverge from silicon.

Why Tapeout

Vendor-neutral. Cross-stack. No embedded IP required.

Works with any EDA stack

PrimeTime or Tempus. TestMAX or Tessent. Any foundry, any tester, any STDF output. No tool lock-in.

No proprietary monitors required

Works with whatever instrumentation already exists — ring oscillators, path monitors, PVT sensors, ATPG patterns.

On-prem / VPC deployment

Semiconductor-grade security. Your design data never leaves your network. Air-gap compatible.

Interpretable results

Every recommendation shows the variables, the evidence, and the affected design objects. No black-box neural network verdicts.

Closing the loop between signoff and silicon.

We’re working with design partners at leading chip companies. If your team spends weeks correlating post-silicon measurements with pre-silicon predictions, let’s talk.