>If primitives don't map naturally to the hardware, then you have to build a runtime to emulate those primitives, just like GC'd languages do.

That's only half the equation. Hardware cannot save you from semantics that are less efficient. To use your example: every GC'd language must have a runtime system track objects, whether that is implemented with or without hardware support. That system constitutes additional overhead -- either precious silicon is used delivering hardware support for GC or clock cycles are used emulating that support. Either way, you're losing performance. C/C++ have semantics that are easy to support, in contrast.

>You cannot run any arbitrary C program on a GPU.

Nor can you run any arbitrary C/C++ program written for Posix on Windows, or a program written for the x86 on a STM32, etc. You have always had to know your platform with C/C++. The point is that they are flexible enough to work very well on many platforms.

>This fact is exactly why GPUs were able to innovate without legacy compatibility holding them back.

GPUs have become a lucrative business precisely because they have begun exposing a C++ interface. Look at how the usage of graphics cards have changed in recenter years.

> If C were so perfectly suited to any sort of hardware, then GPUs would have been able to run C programs right from the beginning, which is not true.

No. GPUs _were not_ general purpose compute devices from the beginning, as you pointed out. You had GLSL, etc. but the interface exposed to programmers was not Turing-complete. From what I gather, GPUs have only had a Turing-complete interface since shader model 3.0, which first appeared in 2004. By 2007, you had nvcc. Today, C++ is very well supported by CUDA. You may as well be saying "You can't run C on a cardboard box, so it's obviously not well-suited to all hardware." Obviously, your hardware needs to expose a Turing-complete interface for a Turing-complete language to be able to run on it.

>The problem is that C was given a disproportionately heavy weighting in these decisions. For instance, a tagged memory architecture would show zero improvement on C benchmarks, but it would have been huge for the languages that now dominate the software industry.

At what cost? As I already pointed out, adding support for VHLLs at the hardware level means you are spending silicon space on that task => languages like C will be slower. Yes, a lot of software is written in JavaScript, Java, and Python, and these languages would benefit from that hardware support. But people using JavaScript, Java, and Python generally are relying on C services (memcached, redis, postgre, etc) to do their heavy-lifting anyway, which you just made slower.

>For instance, who would create a hardware architecture that didn't have pointers? It would simply never happen, because efficient C compatibility is too important.

No. It would never happen because the machine you just described would make a very bad general purpose computer.

>The limitations of C are well known

Yes, they are. But everything you listed isn't substantial. It's C, with a better standard library, standard support for controlling alignment/padding, and modules. That's not significantly different.