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.

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swerner 2 hours ago | parent [-]

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.

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anon291 an hour ago | parent [-]

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.

	▲	swerner 25 minutes ago \| parent [-]
		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.