The client’s system featured a digital microscope utilizing custom GStreamer filters to enhance video quality. However, enabling these filters introduced latency issues that impacted real-time performance. We analyzed the contribution of each filter to the overall pipeline delay and applied optimization techniques to reduce their processing time. Leveraging new NVIDIA® resource management and optimized internal color conversions, we successfully reduced pipeline latency by 20%, improving it from 37 ms to 30 ms.
Proposed solutions
Cutting latency with smarter pipelines
Optimizing custom CUDA filters for real-time performance
We optimized the custom CUDA filters integrated as GStreamer plugins to reduce their processing latency, resulting in a more efficient video pipeline.
For a deeper look at how we approach latency challenges in embedded pipelines, read our article Reducing video latency for GStreamer filters in digital microscopes, where we share additional techniques that complement the work done in this project.
Proposed solutions
Cutting latency with smarter pipelines
Optimizing custom CUDA filters for real-time performance
We optimized the custom CUDA filters integrated as GStreamer plugins to reduce their processing latency, resulting in a more efficient video pipeline.
For a deeper look at how we approach latency challenges in embedded pipelines, read our article Reducing video latency for GStreamer filters in digital microscopes, where we share additional techniques that complement the work done in this project.