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Course contents

  • How to Use This Course
  • AI-VLSI Metrics Reference
  • AI-VLSI Glossary
  • Reading Path
  • ML Math Foundations61
  • Neural Networks Basics61
  • Training Data Pipeline61
  • AI Compute Hardware61
  • Accelerator Architecture61
  • AI in VLSI Workflows61
  • Edge Deployment & MLOps61
  • AI-VLSI Interview Prep4
  • AI Basics for VLSI Engineers Cheatsheet
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‹AI for VLSI
  1. Topics
  2. AI for VLSI
  3. AI Basics for VLSI Engineers Cheatsheet

AI for VLSI · All levels

AI Basics for VLSI Engineers Cheatsheet

Dense reference for model-mechanism debugging, hardware-aware tradeoffs, and deployment decisions.

Debug order

Diagram
METRIC -> MECHANISM -> ARTIFACT -> OWNER -> DECISION

Context: workload slice + revision tags
Model: quality + calibration + convergence behavior
Hardware: utilization + bandwidth + precision impact
Workflow: signoff-correlation + confidence gating
Deployment: compatibility + monitoring + rollback

Questions before proposing a fix

  1. Which metric and workload slice regressed first?

  2. Is root cause in data, model, runtime, or hardware mapping?

  3. Which artifact proves mechanism rather than assumption?

  4. Who owns the smallest reversible fix?

  5. What validation + rollback gates protect release quality?

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See also

  • How to Use This Course
  • AI-VLSI Metrics Reference
  • AI-VLSI Glossary