7. Hardware Accelerator

In the field of AI frameworks, hardware accelerators play a vital role in enabling efficient neural network computations. This chapter delves into the design of modern hardware accelerators, their programming techniques, and the typical approaches to optimize accelerator performance.

This chapter has the following learning objectives:

1. Understand the architecture of a modern hardware accelerator.

2. Understand the methods of programming hardware accelerators.

3. Understand the typical techniques used to optimize the performance of accelerators.

• 7.1. Overview
• 7.2. Components of Hardware Accelerators
  • 7.2.1. Architecture of Accelerators
  • 7.2.2. Memory Units
  • 7.2.3. Compute Units
  • 7.2.4. Domain Specific Architecture
• 7.3. Programming Methods
  • 7.3.1. Method Classification
  • 7.3.2. Programming Examples
• 7.4. Performance Optimization Methods
  • 7.4.1. Implementing General Matrix Multiplication
  • 7.4.2. Enhancing Arithmetic Intensity
  • 7.4.3. Caching Data in Shared Memory
  • 7.4.4. Reducing Register Usage
  • 7.4.5. Hiding Shared Memory Loading Latency
  • 7.4.6. Hiding Global Memory Loading Latency
  • 7.4.7. Performance Optimization Principles
• 7.5. Chapter Summary