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Comment by Alifatisk | Hacker News Reader

I’ve been looking for more ways to speedup the transcoding process, one solution I found was using gpu acceleration, another was using more threads but its hard to find the optimal amount I should provide.

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Can't you just use Hyperparameter Optimization to find the best value? Tools like Sherpa or Scikit-optimize can be used to explore a search space of n-threads/types of input/CPU type (which might be fixed on your machine).

I don't think "just" is appropriate here, that makes it sound like this should be a trivial task for anyone while it is not. Using "just" like this minimizes work and makes people feel stupid which leads to various negative outcomes.

Sorry for lecturing

For most workloads, setting the number of threads to the number of vCPUs (i.e. count each hyperthreaded core as 2) works. But GPU acceleration is much better if it's available to you.

Though in my tests I found that gpu acceleration of video decoding actually hurts performance. It seems software decoding is faster than hardware for some codecs. Of course not the case for encoding.

That heavily depends on the GPU being used and whether or not it has hardware support for your codec. Maybe your GPU is just old/weak compared to your CPU?

That's possible, but if you look at nvidia, the whole range uses the same hardware accelerator, so at most it is a difference in term of chip generation, not so much GPU model.

I am not saying GPU hw decoding isn't useful, it certainly is in term of power consumption, and the CPU might be better used for something else happening at the same time. But in term of raw throughput it's not clear that a GPU beats a recent CPU.

wouldn't that only be true if your hardware doesn't have the decoder isn't built into the hardware of your gpu?

GPU acceleration may produce worse quality and slightly larger files. So there's a trade-off to be had.

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