CUDACasts Episode 21: Porting a simple OpenCV sample to the Jetson TK1 GPU

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In the previous CUDACasts episode, we saw how to flash your Jetson TK1 to the latest release of Linux4Tegra, and install both the CUDA toolkit and OpenCV SDK.  We’ll continue exploring the power efficiency the Jetson TK1 Kepler-based GPU brings to computer vision by porting a simple OpenCV sample to run on the GPU.  We’ll explore computer vision further in a future CUDACast when we look at the VisionWorks toolkit from NVIDIA.

CUDACasts are short how-to screencast videos about new features and techniques for GPU programming. Click here for all CUDACasts.

To suggest a topic for a future episode of CUDACasts, or if you have any other feedback, please use the contact form or leave a comment below.

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About Mark Ebersole

As CUDA Educator at NVIDIA, Mark Ebersole teaches developers and programmers about the NVIDIA CUDA parallel computing platform and programming model, and the benefits of GPU computing. With more than ten years of experience as a low-level systems programmer, Mark has spent much of his time at NVIDIA as a GPU systems diagnostics programmer in which he developed a tool to test, debug, validate, and verify GPUs from pre-emulation through bringup and into production. Before joining NVIDIA, he worked for IBM developing Linux drivers for the IBM iSeries server. Mark holds a BS degree in math and computer science from St. Cloud State University. Follow @cudahamster on Twitter
  • Chim Lee Cheung

    The last demo is optical flow? Is it running in real time?

  • Augustine Wong

    Hi,

    Can you have a future cudacast in which you demonstrate how to perform cross compilation with a Jetson? Many of the online resources I found describe how to install a cross-compilation platform on the host system but don’t walk through the entire process of installing the cross-compilation platform, compiling CUDA programs on the host, and placing those programs onto Jetson.

    Thanks!