AI-Assisted Hardware Verification
Cognitive Verification Architecture with the VEGA Framework
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Beschreibung
This book offers a structured methodology for applying generative AI to the functional verification of complex semiconductor designs, without sacrificing engineering accountability. It presents the VEGA framework—Verification Engineering through Guided AI—a complete verification lifecycle that treats AI as a governed accelerator, preserving traceability between design intent and verification evidence from specification through silicon sign-off.
Provides verification architects with a reliable framework to reduce pain of “ungoverned AI”
Describes prompts, templates, and quality gates, drawn from actual design verification challenges
Offers first comprehensive, methodologically grounded treatment of AI-assisted hardware verification
"VEGA arrives at exactly the right moment, when AI tools are powerful enough to transform verification productivity but undisciplined enough to undermine it. Vikash's intent-centric framework equips verification engineers, team leads, and architects to maintain quality and traceability from test plan through sign-off. A must-read for every hardware verification professional." — Gaurav Jalan, Vice President, Engineering, Marvell
"AI is becoming part of verification, but using it without structure can create more risk than value. Vikash's VEGA framework gives engineers a practical way to apply AI while preserving design intent, traceability, review discipline, and human accountability. This is a timely and useful book for verification engineers, leads, and students looking to understand where AI-assisted verification is heading." — Yunus Akhtar, Senior SoC Verification Engineer, Microsoft
"What stands out is the discipline. This isn't AI as a shortcut, it's AI as a governed accelerator, with verification quality made measurable rather than asserted and sign-off reframed as an evidence-based argument you can actually defend. Essential reading for any architect or lead bringing LLMs into a serious verification flow." — Manish Tanwar, DV Architect, AMD
This book offers a structured methodology for applying generative AI to the functional verification of complex semiconductor designs, without sacrificing engineering accountability. It presents the VEGA framework—Verification Engineering through Guided AI—a complete verification lifecycle that treats AI as a governed accelerator, preserving traceability between design intent and verification evidence from specification through silicon sign-off.
Provides verification architects with a reliable framework to reduce pain of “ungoverned AI”
Describes prompts, templates, and quality gates, drawn from actual design verification challenges
Offers first comprehensive, methodologically grounded treatment of AI-assisted hardware verification
"VEGA arrives at exactly the right moment, when AI tools are powerful enough to transform verification productivity but undisciplined enough to undermine it. Vikash's intent-centric framework equips verification engineers, team leads, and architects to maintain quality and traceability from test plan through sign-off. A must-read for every hardware verification professional." — Gaurav Jalan, Vice President, Engineering, Marvell
"AI is becoming part of verification, but using it without structure can create more risk than value. Vikash's VEGA framework gives engineers a practical way to apply AI while preserving design intent, traceability, review discipline, and human accountability. This is a timely and useful book for verification engineers, leads, and students looking to understand where AI-assisted verification is heading." — Yunus Akhtar, Senior SoC Verification Engineer, Microsoft
"What stands out is the discipline. This isn't AI as a shortcut, it's AI as a governed accelerator, with verification quality made measurable rather than asserted and sign-off reframed as an evidence-based argument you can actually defend. Essential reading for any architect or lead bringing LLMs into a serious verification flow." — Manish Tanwar, DV Architect, AMD
Provides verification architects with a reliable framework to reduce pain of “ungoverned AI” Describes prompts, templates, and quality gates, drawn from actual design verification challenges Offers first comprehensive, methodologically grounded treatment of AI-assisted hardware verification
Autor*in
Vikash Kumar
Themen in »AI-Assisted Hardware Verification«
Large language models in functional verification UVM testbench generation using AI SystemVerilog verification with LLM automation Intent-driven hardware verification framework Generative AI for SoC verification