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My next big endeavour with Quaint will be to create a clean module and linking system (without header files or any textual inclusions). Each source file will be transformed to a corresponding unit which contains code, data and exported type definitions. The linker would then merge these units and produce a native executable that runs your program in the self-hosted VM which will be a part of that executable. Pure native compilation or LLVM integration is too much of a hassle for me at this point.

One of the virtues of the language would also be the direct correspondence between the HLL code and the emitted VM instructions, without any optimisation passes. This makes it much easier to reason about code performance and to write code which performs consistently and predictably (albeit a bit slower).

Nim fits everything you ask, except for "can target GPUs via LLVM or SPIR-V". Even that may eventually be fixed by having OpenCL C as a compilation target.

Also, I am not sure what you mean by "first class SIMD structures", but you can definitely have a single definition for sin4f and sin8f if they are line by line equal except types, by using union types.

Nim is definitely on my short list of languages to learn, however...

Targetting GPUs is a deal-breaker. I'm sure the Nim compiler would be pretty easy to retarget to GPUs via SPIR-V (the new binary IR for Vulkan/OpenCL shaders and kernels) or OpenCL/CUDA C. But I don't think that would work for Nim's runtime system or existing Nim libraries (including any standard libs it has).

Also Nim's pauseless low latency automatic memory management (I guess you can call it a "GC") is very interesting but it's not what I'm after.

> Also, I am not sure what you mean by "first class SIMD structures",

I mean this:

    def multiply_and_add(a : <n x f32>, b : <n x f32>, c : <n x f32>) : <n x f32> {
        return (a*b) + c;
        // TODO: figure out how to use "madd" from FMA4 or NEON instruction set
    }

The trivial piece of code above should be "generic" so that it can be called with any width of vector.

Now the example above is very trivial but more complex examples might have challenges for correct implementation of the type checker. In particular, doing vector shuffles (ie. equivalent __builtin_shufflevector in GCC/Clang vector extensions) would need to have a strange type. Shader languages typically use a syntax like `myvector.wxzy`, which might work.

This might perhaps be possible with an ungodly mess of C++ templates and explicit template specialization for each vector type (and hoping that the compiler is aggressive enough in inlining). But I'm not really a fan of template-heavy C++.

In fact, the kind of solution I've been thinking about would be semantically similar to what I'd do with C++ templates.

> but you can definitely have a single definition for sin4f and sin8f if they are line by line equal except types, by using union types.

I'm not familiar enough with Nim's union types to be sure, but my guess is that this would not compile to efficient low level code apart from the most trivial of circumstances. This is my (not very) educated guess based on other high level languages with some concept of union types.

Anyway, Nim is a very cool language that I will check out sometime in the near future. It just isn't what I'm looking for my very specific use case.

A union type in Nim can only be used in funciton arguments, and it does the obvious thing: when you actually call the function, it specializes to the type you are calling with. Think about templates in C++, where the type parameter can only assume one of two (or more) values. Hence it would generate exactly what you would write by hand, but the syntax is much less messy than C++ templates

Zig (https://github.com/andrewrk/zig), "a system programming language intended to replace C", has a lot of those features.

You might also be interested in Jai [0] which has many of those things but is not a 'real language' yet or possibly ever. Lots of interesting ideas though.

[0]: https://github.com/BSVino/JaiPrimer/blob/master/JaiPrimer.md

You've almost described ISPC verbatim. If you don't already know about it you might want to check it out. http://ispc.github.io/index.html

It doesn't compile to a native executable, but since it produces .o files you should be able to just set your entry point and go from there.

> You've almost described ISPC verbatim.

Thanks, I've read about it before, but haven't spent too much time looking at it.

However, this "single program, multiple data" isn't exactly what I'm looking for (it would solve the sin4f vs. sin8f issue mentioned above, though). I need explicit, low level access to SIMD, coupled with genericity over vector widths. This means doing almost assembly-style SIMD code with explicit shuffles, blending, etc as well as access to intrinsics where needed.

I also need portability (ispc is from Intel, it probably doesn't support ARM NEON) and targetting GPUs.

I'm very well aware that my needs are very specific. I need to do math stuff for 3d graphics and physics applications.

All I need is for a lot of free time to appear from out of nowhere and I can write a prototype compiler for this myself :)

How would you use specific instructions yet have widths abstracted?

ISPC actually has some preliminary support for targeting Nvidia PTX btw. It compiles using LLVM.

See example above in this thread. In C + GCC vector extensions, I just use normal arithmetic operations (+, -, *, /).

However, when using specific intrinsics they are for a specific width. It might take some "library code" to take advantage of some instructions like dot products, etc.

Julia has all these things