It's impossible to have an open standard. Hardware accelerators are nothing alike and have different perf characteristics. Each kernel is tuned to the hardware. The idea of writing a performant kernel in opencl is a fantasy.
Source: worked at a bunch of accelerator companies in the kernels or equivalent team. They're nothing alike.
C ran on computers with 8/12/16/18/24/32/36/48/60 bit words, computers with 8/9-bit bytes, 6/9 bit characters, computers with word and byte addressing, with one's and two's compliment integers, with flat and non-flat memory models, with different endianness & different alignment rules.
Early graphics APIs ran on GPUs that were just about as different form one another as that.
We could easily figure it out, were it not for the trillion dollars incentives to not figure it out.
For a performant portable language, we’d have to go to a higher level where you describe what to do and leave the how to do to the compiler. It would then need to be able to adjust memory layout, access patterns, data type choice to the underlying hardware. I’m not sure if this is possible to do reliably - the closest we have right now may in fact be highly detailed plain English descriptions of the algorithms fed to an LLM prompted to produce assembly.
It's not possible to do reliably. None of the models in current use today use any esoteric math. It's extremely easy to implement the math behind both the inference and learning of all modern models.
Not everything is AI and dot products of massive vectors, there are still applications that do other maths on GPUs
My thinking was rather that most of our current programming languages put memory layout fully into the programmer’s responsibility - I can think off hand of a language where the compiler makes performance decisions like whether your structure are SoA, AoS or SoAoS, what alignment, padding, strides and float types to use.
Automatic decisions about when to use cooperative loads through shared local mem versus gathers from global mem and hardware caches are also something that such a hypothetical compiler would have to make.
I mean if you don't care about perf, opencl does what you want, and exists today.
As for ai and matrix vector performance... I mean matrices are extremely useful across many domains. The hands off language that exists today is called blas. That's fine but won't lead to the best perf on any GPU today.
SoA and AoS data layouts are not even a worthwhile point of contention. Same with shared v global mem. Today's hardware has specialized memory depending on the operation. The hardware on these processors is so specialized as to make anything but first class support for the feature be completely pointless. If you look at Nvidia code that's open source even they will special case a lot of their chips. Literally if you want the best perf you write the kernel exactly for the exact chip. That's intra vendor .. you can only imagine inter vendor