# Profile Applications


To get the most out of your AI system using OpenVINO, OVMS, or DL Streamer, you may consider
profiling it. You can do it with [Intel® VTune™ Profiler](https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html)
that will enable you to analyze CPU/GPU usage, kernel execution, threading, memory bottlenecks,
and overall performance of your code. Supporting multiple programming languages, it will help
you identify inefficient algorithm and hardware usage, as well as give tuning advice.

Check out its [User Guide](https://www.intel.com/content/www/us/en/docs/vtune-profiler/user-guide/2025-4/overview.html)
to learn more about its features and workflow, or [Get Started](https://www.intel.com/content/www/us/en/docs/vtune-profiler/get-started-guide/2025-4/overview.html) right away. The process is easy, for example, based on the
[DL Streamer Profiling Guide](https://docs.openedgeplatform.intel.com/2025.1/edge-ai-libraries/dl-streamer/dev_guide/profiling.html):


- [Download Intel® VTune™ Profiler](https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler-download.html)
  and install it.
- Make sure your system has the appropriate Intel CPU/GPU drivers for your hardware.
- Since ITT instrumentation is enabled in the default builds of DL Streamer, just use the
  following command:


  ```bash
  GST_DEBUG=3 ./your_pipeline.sh
  vtune -collect hotspots -result-dir dlstreamer_results ./your_pipeline.sh
  ```
  or, for pipelines that require heavy GPU/accelerator, such as OpenVINO on GPU:

  ```bash
  vtune -collect gpu-hotspots -result-dir dlstreamer_gpu ./your_pipeline.sh
  ```