AI Hardware Engineering

ChatStick Co., Ltd.

About this app

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.

What’s new

Version 1.0