Contents

• 1. CUDA for Tegra
• 2. Overview
• 3. Memory Management
  • 3.1. I/O Coherency
  • 3.2. Estimating Total Allocatable Device Memory on an Integrated GPU Device
• 4. Porting Considerations
  • 4.1. Memory Selection
  • 4.2. Pinned Memory
  • 4.3. Effective Usage of Unified Memory on Tegra
  • 4.4. GPU Selection
  • 4.5. Synchronization Mechanism Selection
  • 4.6. CUDA Features Not Supported on Tegra
• 5. EGL Interoperability
  • 5.1. EGLStream
    • 5.1.1. EGLStream Flow
    • 5.1.2. CUDA as Producer
    • 5.1.3. CUDA as Consumer
    • 5.1.4. Implicit Synchronization
    • 5.1.5. Data Transfer Between Producer and Consumer
    • 5.1.6. EGLStream Pipeline
  • 5.2. EGLImage
    • 5.2.1. CUDA interop with EGLImage
  • 5.3. EGLSync
    • 5.3.1. CUDA Interop with EGLSync
    • 5.3.2. Creating EGLSync from a CUDA Event
    • 5.3.3. Creating a CUDA Event from EGLSync
• 6. CUDA Upgradable Package for Jetson
  • 6.1. Installing the CUDA Upgrade Package
    • 6.1.1. Prerequisite
    • 6.1.2. From Network Repositories or Local Installers
  • 6.2. Deployment Considerations for CUDA Upgrade Package
    • 6.2.1. Use the Right Upgrade Package
    • 6.2.2. Feature Exceptions
    • 6.2.3. Check for Compatibility Support
• 7. cuDLA
  • 7.1. Developer Guide
    • 7.1.1. Device Model
    • 7.1.2. Loading and Querying Modules
    • 7.1.3. Memory Model
    • 7.1.4. Task Execution and Synchronization Model
    • 7.1.5. Error Reporting Model
  • 7.2. Migrating from NvMediaDla to cuDLA
  • 7.3. Profiling a cuDLA App
  • 7.4. cuDLA Release Notes