Traces

Notes from the silicon engineering floor.

Writing on physical design automation, AI-driven EDA flows, and lessons from tape-out with hardware teams.

Why We Built AI Above the Physical Design Stack

AI does not replace your EDA tools. It operates as a coordination layer on top of them. We explain how that boundary works and why it matters for teams evaluating AI-assisted flows.

ECOs: The Hidden Cause of Tape-Out Delays

ECOs are unavoidable. But the delay they cause is often not from the fix itself, it is from re-running verification for changes that could have been confined to a smaller sub-region.

Verification Without a 20-Person Silicon Team

A three-person layout team cannot run every verification pass manually. A framework for deciding which checks to automate, which to gate on, and which to escalate to external review.

Cell Library Choices Before P&R

P&R tools are better than ever at routing. The slowdown is in the cell selection decisions that happen before routing begins. Where AI can reduce that overhead without trading QoR.

Our Approach to Timing Closure in AI Hardware Blocks

AI accelerator chips have dataflow patterns that make classic STA assumptions break down. The constraint strategies that work for general-purpose logic often make closure harder, not easier, on systolic arrays and tensor engines.

Fewer RTL-to-GDS Iterations: A Practical View

Early adopters of AI-assisted physical design have been running full tape-out flows since mid-2025. A look at the iteration count data and where the reduction actually comes from.

The Real Price of Late DRC

A DRC violation caught early is a routing change. Caught at sign-off, it can be a full re-spin. We break down the time and cost economics of late-stage DRC discovery across process nodes.

How Small Teams Reach Custom Silicon Tape-Out

The toolchain required to tape out custom silicon was built for large semiconductor companies. We look at the friction points small teams hit most often and how the landscape is starting to shift.