The MATLAB Coder™ Support Package for NVIDIA® Jetson™ and NVIDIA DRIVE® Platforms enables you to deploy your MATLAB function on the hardware. The function is deployed as a standalone executable that continues to run even if the hardware live connection is disconnected from the host computer.
|Connection between audio input device and NVIDIA hardware (Since R2021a)
|Connection between audio output device and NVIDIA hardware (Since R2021a)
|Capture data from audio device connected to NVIDIA hardware (Since R2021a)
|Play audio from audio device connected to NVIDIA hardware (Since R2021a)
|Connection to USB or CSI camera (Since R2019a)
|Get a list of available cameras on the NVIDIA hardware (Since R2019a)
|Get a list of available audio devices on the NVIDIA hardware (Since R2021a)
|NVIDIA display object
|Capture RGB image from Camera
|Scan for and update the list of peripherals connected to the target hardware
|Connection to a Velodyne LiDAR sensor (Since R2022b)
|Acquire point clouds from
buffer (Since R2022b)
|Start streaming point clouds from Velodyne LiDAR sensor (Since R2022b)
|Stop streaming point clouds from Velodyne LiDAR sensor (Since R2020b)
|Connection to USB web camera
|Open terminal on host computer to use a Linux shell on NVIDIA hardware
|Run commands in a Linux shell on the NVIDIA hardware
|Get the L4T version of the NVIDIA Jetson hardware
|Get the version number of the DriveWorks SDK installed on the NVIDIA DRIVE hardware
|Get the display environment value used for redirecting the display on the target (Since R2019a)
|Set the display environment value used for redirecting the display on the target (Since R2019a)
|Select the target hardware to build code for from multiple live connection objects
|Get information about the Linux environment on the target
|Kill an application on the NVIDIA target by name (Since R2019a)
|Kill a process on the NVIDIA target by ID (Since R2019a)
|Launch an application on the NVIDIA target by name (Since R2019a)
|Launch an executable on the NVIDIA target by name (Since R2019a)
|Set the timeout value that PIL uses for reading data (Since R2019a)
|Set the TCP/IP port number used by the PIL execution (Since R2019a)
|Get the timeout value that PIL uses for reading data (Since R2019a)
|Get the TCP/IP port number used by the PIL execution (Since R2019a)
- Build and Run an Executable on NVIDIA Hardware
Build and run an executable on NVIDIA hardware.
- Build and Run an Executable on NVIDIA Hardware Using GPU Coder App
Use GPU Coder™ app to build and run an executable on NVIDIA hardware.
- Read Video Files on NVIDIA Hardware
Generate CUDA® code for reading video files on the NVIDIA target by using the
- Stop or Restart an Executable Running on NVIDIA Hardware
Stop or restart an executable running on the hardware.
- Processor-In-The-Loop Execution from Command Line
Use PIL execution to verify the numerical behavior of the generated code at the MATLAB command line.
- Processor-In-The-Loop Execution with the GPU Coder App
Use the GPU Coder app to verify the numerical behavior of the generated code.
- Execution-Time Profiling for PIL
Why measure execution times for code generated from entry-point functions.
- Targeting NVIDIA Embedded Boards (GPU Coder)
Build and deploy to NVIDIA GPU boards.
- Numerical Equivalence Testing (GPU Coder)
Compare results from model and generated code simulations.
- Parameter Tuning and Signal Monitoring by Using External Mode (GPU Coder)
Tune parameters and monitor signals through a TCP/IP communication channel between development computer and target hardware.