PPA Optimization Engine
Profiles timing, power, and area weak spots, ranks source-traceable techniques, and keeps every recommendation tied to evidence.
PPA optimization engine for semiconductor teams
Cut the PPA optimization loop from months to weeks.
RTL Arena gives chip teams a second optimization brain: diagnose weak paths, explain tradeoffs, rank bounded fixes, and prove before/after QoR while engineers keep final control.
Read-only diagnosis firstEngineer approval gatesWorks beside EDA flows
3-4 momanual PPA loop
~2 wktargeted closure sprint
20K+LOC-aware RTL agent
<60mread-only audit target
Three surfaces, one closure loop
Not a chatbot. An optimization workbench with proof.
The product line is built around the final stretch before tape-out: understand the block, explain the path, propose a bounded fix, prove the QoR delta, and preserve the engineer's decision boundary.
RTL Arena Agent
Explains blast radius, produces bounded RTL candidates, and waits for engineer approval before touching customer design files.
Flow Evidence Viewer
Turns compile, lint, synthesis, timing, schematic, and QoR artifacts into one shared review surface for engineers and leadership.
Controlled workflow
A clear path from PPA chaos to a verified closure loop.
Every stage reduces ambiguity: the engine turns scattered EDA artifacts into a ranked, reviewable, and re-verified optimization path.
01ContextRTL / SDC / Liberty
02Profilecritical path ledger
03Rankbounded candidates
04Provebefore / after QoR
Trust orderdiagnose -> explain -> recommend -> compare -> approved change
Step 1Read-only mode
Ingest the live design context
RTL or netlist, Liberty, SDC, constraints, timing reports, synthesis outputs, and available activity assumptions stay mapped to the engineer's environment.
RTL hierarchySDC / LibertyTiming reports
Step 2Baseline profile
Profile PPA weak regions
The engine builds a baseline, traces failing endpoints, highlights path contributors, and separates evidence-backed data from planning-grade estimates.
Critical pathFanoutSlack ledger
Step 3Engineer review
Rank bounded optimization candidates
Each candidate carries rationale, expected direction, risk, files affected, and the checks required before anyone accepts the change.
TechniqueRiskPatch scope
Step 4QoR report
Re-verify and report the delta
Accepted candidates are re-profiled into before/after QoR views so CTOs see effort, tradeoff, evidence grade, and remaining tape-out risk.
Before/afterEvidence gradeRollback
Evidence layer
Every recommendation carries the concern, the control, and the claim boundary.
The landing page intentionally avoids push-button tape-out claims. It frames RTL Arena as a controlled optimization engine that works inside the team's flow and reports only what the evidence supports.
Recommendation packetApproval required
ConcernWNS sink
Controlbounded diff
Claim boundaryplanning-grade
RecheckQoR delta
Will it bypass review?
Guided mode is default. Automated edits require explicit approval, guardrails, and rollback metadata.
Are the numbers signoff-grade?
The page separates evidence-backed indicators from planning-grade estimates until signoff artifacts exist.
Does it replace Cadence or Synopsys?
No. RTL Arena sits beside the existing flow and reduces manual optimization burden.
Why trust an AI tool near tape-out?
The trust order is diagnose, explain, recommend, compare, then change only after approval.
Mock performance numbers
Founder-friendly outcomes, engineer-readable math.
EvidenceB+
Loop count14 -> 5illustrative target
DimensionDeltaEvidence noteStatus
PerformanceFmax +11.8%WNS -0.18 ns -> +0.04 nsMock target
PowerLeakage -6.4%Planning-grade until routed evidenceBoundary visible
AreaCell area -3.1%Drive-strength and fanout tradeoffNeeds review
Iteration14 -> 5 loopsEDA runs avoided on target blockMock target
Who feels the urgency
Built for teams whose chip only wins if its PPA wins.
AI accelerators
Performance-first teams where every Fmax recovery and closure iteration affects the product promise.
Mobile and edge AI
Teams balancing performance with battery, thermals, leakage, and area pressure across constrained designs.
Data-center silicon
Mature organizations where expensive engineers and EDA cycles need a sharper ranked backlog.
Automotive and industrial
Review-heavy flows where explainability, evidence boundaries, and controlled change are non-negotiable.
Pilot posture
Start with one pathological block. Prove the loop before broad rollout.
Day one is intentionally contained: baseline, ranked candidates, guided review, re-verification, report, and clear deferred items.
No raw RTL leaves by defaultApproval before editsBefore/after QoR export
Discuss pilot scope