[GH-ISSUE #702] Update the AI Acceleration chapter #5514

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GiteaMirror · 2026-04-21T21:28:02-05:00

GiteaMirror commented

2026-04-21 21:28:02 -05:00

Originally created by @profvjreddi on GitHub (Feb 10, 2025).
Original GitHub issue: https://github.com/harvard-edge/cs249r_book/issues/702

Originally assigned to: @profvjreddi on GitHub.

Need to update the AI acceleration chapter to map more closely to the new alignment of the book chapters. Have a bunch of updates to push, so creating an issue to branch off of.

My current plan is to do something like this (pending some edits)

Chapter 11: AI Hardware Acceleration

11.1 Overview of AI Hardware Acceleration

Scope and Goals
Key Challenges
Chapter Organization

11.2 Evolution of AI Hardware Accelerators

Historical Context
From CPUs to Specialized Hardware
Current State of the Industry

11.3 Processor Architecture Primitives for ML

Vector Operations
Matrix Operations
Dataflow Patterns
Special Function Units

11.4 Memory Systems for ML Accelerators

Memory Hierarchy Design
Bandwidth and Latency
Data Movement Patterns
Novel Memory Architectures

11.5 Mapping Neural Networks to Hardware

Basic Building Blocks
Neural Network Components
End-to-End Model Mapping

11.6 Optimization Strategies

Performance Analysis and Bottlenecks
Hardware-Specific Optimizations
Model-Specific Optimizations
System-Level Optimizations

11.7 Hardware-Software Co-Design

Design Space Exploration
Model Optimization Techniques
Compiler Stack
Runtime Systems

11.8 Modern AI Accelerator Architectures

GPU Architecture
TPU and Systolic Arrays
FPGA Solutions
Emerging Architectures

11.9 Future Directions

Emerging Hardware Architectures
Novel Computing Paradigms
Research Directions
Industry Trends

11.10 Conclusion

Originally created by @profvjreddi on GitHub (Feb 10, 2025). Original GitHub issue: https://github.com/harvard-edge/cs249r_book/issues/702 Originally assigned to: @profvjreddi on GitHub. Need to update the AI acceleration chapter to map more closely to the new alignment of the book chapters. Have a bunch of updates to push, so creating an issue to branch off of. My current plan is to do something like this (pending some edits) # Chapter 11: AI Hardware Acceleration ## 11.1 Overview of AI Hardware Acceleration - Scope and Goals - Key Challenges - Chapter Organization ## 11.2 Evolution of AI Hardware Accelerators - Historical Context - From CPUs to Specialized Hardware - Current State of the Industry ## 11.3 Processor Architecture Primitives for ML - Vector Operations - Matrix Operations - Dataflow Patterns - Special Function Units ## 11.4 Memory Systems for ML Accelerators - Memory Hierarchy Design - Bandwidth and Latency - Data Movement Patterns - Novel Memory Architectures ## 11.5 Mapping Neural Networks to Hardware - Basic Building Blocks - Neural Network Components - End-to-End Model Mapping ## 11.6 Optimization Strategies - Performance Analysis and Bottlenecks - Hardware-Specific Optimizations - Model-Specific Optimizations - System-Level Optimizations ## 11.7 Hardware-Software Co-Design - Design Space Exploration - Model Optimization Techniques - Compiler Stack - Runtime Systems ## 11.8 Modern AI Accelerator Architectures - GPU Architecture - TPU and Systolic Arrays - FPGA Solutions - Emerging Architectures ## 11.9 Future Directions - Emerging Hardware Architectures - Novel Computing Paradigms - Research Directions - Industry Trends ## 11.10 Conclusion

GiteaMirror added the area: book type: improvement labels 2026-04-21 21:28:02 -05:00

GiteaMirror closed this issue

2026-04-21 21:28:03 -05:00

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Reference: github-starred/cs249r_book#5514