alt Hacker NewsNot 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