Extremely slow ffmpeg/sws_scale() - only on heavy duty

  • 10 months ago
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If you are experiencing extremely slow performance with ffmpeg and sws_scale() when processing heavy-duty tasks, there are several possible reasons for this behavior. Here are some common factors to consider and potential solutions:

  1. Hardware Limitations: Heavy-duty tasks require significant computational resources, and your hardware might not be capable of handling such loads efficiently. Consider using a machine with better CPU and GPU capabilities for resource-intensive tasks.

  2. ffmpeg Version: Ensure that you are using the latest stable version of ffmpeg. Newer versions often come with performance improvements and bug fixes.

  3. Codec and Format: The choice of codec and output format can greatly affect the processing speed. Some codecs are more computationally expensive than others. Experiment with different codecs and formats to find the most suitable combination for your use case.

  4. Optimization Flags: When compiling ffmpeg from source, use appropriate optimization flags to enhance performance on your target platform. For example, using compiler flags like -O3 can help improve performance.

  5. Multithreading: Check if ffmpeg is utilizing multiple threads effectively. You can use the -threads option to specify the number of threads to use during encoding or decoding.

  6. Hardware Acceleration: Take advantage of hardware acceleration features on your system. For example, if your system has a GPU with support for video encoding/decoding (e.g., NVIDIA NVENC, AMD VCE, Intel Quick Sync Video), enable hardware acceleration to offload some of the processing tasks from the CPU to the GPU.

  7. Memory Usage: Check the memory usage during heavy-duty tasks. If your system is running out of memory, it can cause slowdowns due to excessive swapping or cache thrashing. Optimize your code to use memory efficiently.

  8. Disk I/O: If your input/output files are stored on slow storage devices, it can cause a bottleneck during heavy-duty tasks. Consider using faster storage options like SSDs to improve I/O performance.

  9. Frame Resizing: If you are using sws_scale() for frame resizing, ensure that you are using the appropriate interpolation method for your use case. Some interpolation methods are more computationally intensive than others.

  10. Parallel Processing: For large batch processing tasks, consider dividing the workload and processing multiple parts in parallel to utilize all available CPU cores efficiently.

  11. Profiling: Use profiling tools to identify performance bottlenecks in your code. This will help you pinpoint areas that need optimization.

Keep in mind that the actual performance improvement will depend on the specific task, hardware, and software configuration. It's essential to balance the trade-offs between processing time and output quality while optimizing your ffmpeg usage.