CUDA is a powerful technology, incredibly powerful GPU and superb suite of development, debugging and profilin tools. x264 project tried to make it work on their excellent h.264 video encoder (that is blazingly fast with a great video quality on CPU).
They failed, or put it differently, they choose not to use it but consider other way to accelerate encoding such as dedicated hardware accelerators (such as ElGato Turbo.264 HD that I use on my laptop).
There’s many way to follow to use CUDA as H.264 encoder accelerator:
- Put some cpu-hungry algorithm part to GPU. Was their first choise, but this algorithm seems slower on their implementation than CPU counter-part. FAILED!
- Put the whole encoding chain to GPU, but as the most computing-intensive part is actually slower on GPU (as they try to implement it) it’s a loss. FAILED!
- Put the whole encoding chain to GPU, *BUT* give it a different movie part to encode, dynamically, and instead swapping to GPU, aggregate CPU and GPU to do the whole encoding.
The third option is a different way to consider the GPU, not as a co-processor in the middle of a cpu-algorithm, but as an asymmetric computing resource, able to give 10% to 30% performance gain on the whole process.
This is the way I am currently exploring, having in mind to obtain a gain in H.264 encoding over pure-cpu, and to be able to port it to OpenCL with dedicated algorithms for CPU and GPU 