Gaussian blur cpu performance

I have been doing some experiments with PIX since it allows computing image augmentations in the GPU in contrast to torchvision which computes in the CPU and requires multiple workers to avoid bottlenecks. When performing some very simple `timeit` examples I observed a very high time when performing a gaussian blur in the CPU. I created a simple [Colab notebook](https://colab.research.google.com/drive/1UgqZVW2I09pPia2EZKhsZTnvwvucRu3Z?usp=sharing ) to demonstrate these experiments. I even tested transferring the image to CPU before performing the blur but it doesn't seem to make any difference. I was wondering if this is intended and I should not rely on CPU computations at all or if something is yet to be optimized for CPU computation.

Start with the linked Colab notebook and its timeit experiments for Gaussian blur, then trace the CPU execution path used by the blur operation in dm_pix. Compare the CPU and GPU timings and determine whether the observed cost is expected or indicates an optimization opportunity. Done means documenting the cause and agreeing on a concrete performance target or change.

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