Presentation
Breaking the O(N^2) Barrier: AI-Assisted Linear-Time Formal Verification of Deep Pipeline Buffers
DescriptionAchieving full formal sign-off for deep hardware tracking structures—critical components in high-bandwidth networking and AI accelerators—often stalls against a 'Complexity Wall' as pipeline depths increase. Standard Bounded Model Checking (BMC) requires sequential unrolling proportional to latency, leading to an exponential state-space explosion that typically renders proofs inconclusive beyond 32-stages. For an N-stage buffer with W-bit identifiers, the total unrolled state complexity grows by O(N^2×W), quadrupling the verification effort with every depth doubling.
This paper introduces a scalable formal verification methodology that shifts the verification paradigm from deep sequential searching to single-cycle inductive transitions, effectively achieving linear scalability (O(N×W)) . Approach uses LLM-driven "Impact Grading" framework that automates the discovery of high-impact inductive invariants. By categorizing candidate properties into a tiered hierarchy (S/A/B), we isolate a 'Golden Triangle' of invariants—State Mapping, Ingress Consistency, and Control-Path Sync—that bridge the reference model and hardware state.
Experimental results demonstrate a paradigm shift: while standard BMC remains inconclusive at 64 stages, our methodology achieves 100% mathematical convergence in ~50 minutes . Furthermore, we demonstrate deterministic scalability up to 256 stages in approximately 7 hours. This work establishes a repeatable, automated framework for the formal sign-off of high-latency structures previously deemed unreachable.
This paper introduces a scalable formal verification methodology that shifts the verification paradigm from deep sequential searching to single-cycle inductive transitions, effectively achieving linear scalability (O(N×W)) . Approach uses LLM-driven "Impact Grading" framework that automates the discovery of high-impact inductive invariants. By categorizing candidate properties into a tiered hierarchy (S/A/B), we isolate a 'Golden Triangle' of invariants—State Mapping, Ingress Consistency, and Control-Path Sync—that bridge the reference model and hardware state.
Experimental results demonstrate a paradigm shift: while standard BMC remains inconclusive at 64 stages, our methodology achieves 100% mathematical convergence in ~50 minutes . Furthermore, we demonstrate deterministic scalability up to 256 stages in approximately 7 hours. This work establishes a repeatable, automated framework for the formal sign-off of high-latency structures previously deemed unreachable.
Event Type
Engineering Poster
TimeTuesday, July 285:00pm - 6:00pm PDT
LocationDAC Pavilion, Exhibit Floor