3. Numba for CUDA GPUs

• 3.1. Overview
  • 3.1.1. Terminology
  • 3.1.2. Programming model
  • 3.1.3. Requirements
    • 3.1.3.1. Supported GPUs
    • 3.1.3.2. Software
  • 3.1.4. Missing CUDA Features
• 3.2. Writing CUDA Kernels
  • 3.2.1. Introduction
  • 3.2.2. Kernel declaration
  • 3.2.3. Kernel invocation
    • 3.2.3.1. Choosing the block size
    • 3.2.3.2. Multi-dimensional blocks and grids
  • 3.2.4. Thread positioning
    • 3.2.4.1. Absolute positions
    • 3.2.4.2. Further Reading
• 3.3. Memory management
  • 3.3.1. Data transfer
    • 3.3.1.1. Device arrays
  • 3.3.2. Pinned memory
  • 3.3.3. Streams
  • 3.3.4. Shared memory and thread synchronization
  • 3.3.5. Local memory
• 3.4. Writing Device Functions
• 3.5. Supported Atomic Operations
  • 3.5.1. Example
• 3.6. Device management
  • 3.6.1. Device Selection
• 3.7. The Device List
• 3.8. Examples
  • 3.8.1. Matrix multiplication
• 3.9. Debugging CUDA Python with the the CUDA Simulator
  • 3.9.1. Using the simulator
  • 3.9.2. Supported features