The thing I tried experimentally implementing is basically a 128x128 matrix mixer with a little bit of extra processing. On a three-year-old MacBook Pro, the GPU barely had to lift a finger to crunch the data, but the round-trip latency was still high enough that it would struggle to keep up with anything less than a buffer size of 512 or so at 48kHz (which is on the high end for live mic processing). It would be fantastic for offline processing with larger buffers, though.
I haven't tried CUDA or OpenCL, so I don't know if the situation is the same there—but of course they have the problem of vendor support as well.
..however, having a few conversations with more knowledgable people has changed our mind and we're definitely going to give it a try on Metal and Vulkan to see what happens. Should be interesting.
Also, we do know a few people who want to use SOUL to write audio code which does need high parallelism. It's not a super-common use-case for audio, but it does exist.
I don't have any experience with Metal or Vulcan but my intuition is that audio DSP is going to include a healthy dose of linear algebra and multi-variate calculus. That points towards some kind of fit with the GPU. Given that basic GPUs are available on practically every device (including phones) it seems like a fantastic fit. Even audio hardware developers would benefit since it would open up access to commodity priced chips (rather than custom asic/fpga/whatever).
And even for very simple audio loads, there's often unused capacity in compute cores (even when running games) which would could do the job "for free" without bothering the CPU.