Multi-threaded raw video conversion and scaling in GStreamer

Another new feature that landed in GStreamer already a while ago, and is included in the 1.12 release, is multi-threaded raw video conversion and scaling. The short story is that it lead to e.g. 3.2x speed-up converting 1080p video to 4k with 4 cores.

I had a few cases where a single core was not able to do rescaling in real-time anymore, even on a quite fast machine. One of the cases was 60fps 4k video in the v210 (10 bit YUV) color format, which is a lot of bytes per second in a not very processing-friendly format. GStreamer’s video converter and scaler is already quite optimized and using SIMD instructions like SSE or Neon, so there was not much potential for further optimizations in that direction.
However basically every machine nowadays has multiple CPU cores that could be used and raw video conversion/scaling is an almost perfectly parallelizable problem, and the way how the conversion code was already written it was relatively easy to add.

The way it works now is similar to the processing model of libraries like OpenMP or Rayon. The whole work is divided into smaller, equal sub-problems that are then handled in parallel, then it is waiting until all parts are done and the result is combined. In our specific case that means that each plane of the video frame is cut into 2, 4, or more slices of full rows, which are then converted separately. The “combining” step does not exist, all sub-conversions are directly written to the correct place in the output already.

As a small helper object for this kind of processing model, I wrote GstParallelizedTaskRunner which might also be useful for other pieces of code that want to do the same.

In the end it was not much work, but the results were satisfying. For example the conversion of 1080p to 4k video in the v210 color format with 4 threads gave a speedup of 3.2x. At that point it looks like the main bottleneck was memory bandwidth, but I didn’t look closer as this is already more than enough for the use cases I was interested in.

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