AI Hardware Engineering

Design AI accelerators from workload to silicon — completely offline. AI Hardware Engineering is a premium, ad-free toolkit for hardware designers, system architects, VLSI engineers, compiler developers, and students who want to understand and design the chips behind modern machine learning. Everything runs on-device: no account, no internet, no tracking. ★ 15 INTERACTIVE ENGINEERING CALCULATORS Get fast, defensible estimates with clear GOOD / WARN / BAD guidance: • Roofline Estimator — classify a workload as compute- or bandwidth-bound • Tensor Throughput — dense matrix engine peak TOPS • Memory Bandwidth Planner — size HBM traffic for weights and activations • Systolic Array Utilization — padding waste on TPU-style arrays • Power & Thermal Budget — package temperature margin • Inference Latency — memory-bound decode latency per token • Energy Efficiency — TOPS per watt and energy per operation • Quantization Savings — memory saved by lowering precision • KV Cache Size — attention cache for long context • All-Reduce Time — collective sync across accelerators • Training Compute — accelerator-days for a training run • Cost per 1M Tokens — serving energy cost • Power Supply Sizing — PSU headroom and efficiency • Cooling Airflow — airflow to remove board heat • Arithmetic Intensity — FLOPs per byte and machine balance ★ COMPLETE 12-CHAPTER OFFLINE HANDBOOK A full engineering reference that travels with you — no signal required: 1. AI Workload Characterization 2. GPU Microarchitecture for Deep Learning 3. TPU Architecture: Systolic Arrays & Dataflow 4. NPU Architecture & On-Chip Memory 5. HBM, SRAM & Memory Hierarchy 6. Network-on-Chip & Inter-Chip Interconnects 7. Power Delivery & Thermal Management 8. MLIR & Compiler Co-Design 9. Performance Modeling & Roofline Analysis 10. Inference Optimization: Quantization, Sparsity & Deployment 11. Silicon Bring-Up & Post-Silicon Validation 12. Future Trends: In-Memory Computing, Photonics & Chiplets Adjustable reader font size, bookmarks, and read-progress tracking. ★ SILICON LAB ROADMAP A 21-step, 5-phase decision checklist — from workload fit to bring-up — so you can turn theory into an actual design plan and track your progress. ★ LEARN & TEST YOURSELF • 37 chapter quiz questions with instant scoring and pass tracking • 23-term glossary of AI hardware vocabulary • Chapter image gallery • 13 achievements to unlock as your architecture intuition grows ★ FREE BONUS 16 free "Nova" stickers — a thank-you gift you can share with friends and teammates. ★ WHY YOU'LL LIKE IT • 100% offline — works on a plane, in a lab, or a secure facility • No ads, no subscriptions, no data collection • Clean Material 3 design, light & dark themes • Optimized for phones and tablets Whether you are studying tensor cores, sizing HBM bandwidth, estimating thermal margin, or planning first silicon, AI Hardware Engineering puts a working accelerator design lab in your pocket. Made by ChatStick Company Limited.