37 citations · 47 across the 7 of their papers we have counts for
8 papers
Formal-Verification-Guided Bayesian Optimization for Non-Intrusive Last-Mile Coverage Closure
Chengjia Liu, Priyadarsi Mishra, David Kebo Houngninou +3
Last-mile functional coverage closure for modern chip designs remains costly because a mature UVM environment exposes many controls while direct hits on the remaining bins are spar…
Energy per Successful Goal: Goal-Level Energy Accounting for Agentic AI Systems
Deepak Panigrahy, Aakash Tyagi, Stephen Abkin +2
Current AI energy benchmarks measure consumption per model invocation. For agentic systems, where a single user goal may trigger multistep orchestration, tool calls, retries, and f…
The Energy Blind Spot: NVIDIA's Flagship Edge AI Hardware Cannot Support Process-Level Energy Attribution
Deepak Panigrahy, Aakash Tyagi
Agentic AI workloads - where a single user goal triggers multi-step orchestration, tool calls, retries, and failure recovery - are being targeted for edge deployment, with NVIDIA,…
BugGen: A Self-Correcting Multi-Agent LLM Pipeline for Realistic RTL Bug Synthesis
Surya Jasper, Minh Luu, Evan Pan +4
Hardware complexity continues to strain verification resources, motivating the adoption of machine learning (ML) methods to improve debug efficiency. However, ML-assisted debugging…
VCDiag: Classifying Erroneous Waveforms for Failure Triage Acceleration
Minh Luu, Surya Jasper, Khoi Le +4
Failure triage in design functional verification is critical but time-intensive, relying on manual specification reviews, log inspections, and waveform analyses. While machine lear…
Spec2Assertion: Automatic Pre-RTL Assertion Generation using Large Language Models with Progressive Regularization
Fenghua Wu, Evan Pan, Rahul Kande +5
SystemVerilog Assertions (SVAs) play a critical role in detecting and debugging functional bugs in digital chip design. However, generating SVAs has traditionally been a manual, la…
HyPFuzz: Formal-Assisted Processor Fuzzing
Chen Chen, Rahul Kande, Nathan Nguyen +4
Recent research has shown that hardware fuzzers can effectively detect security vulnerabilities in modern processors. However, existing hardware fuzzers do not fuzz well the hard-t…
TheHuzz: Instruction Fuzzing of Processors Using Golden-Reference Models for Finding Software-Exploitable Vulnerabilities
Aakash Tyagi, Addison Crump, Ahmad-Reza Sadeghi +4
The increasing complexity of modern processors poses many challenges to existing hardware verification tools and methodologies for detecting security-critical bugs. Recent attacks…