std-simd VS nsimd

neither proposing nor taking a position on this possible addition)

> ... For completeness we would also like to add that a serious issue is that C still lacks vector operations.

Those are good points. The authors don't take a stance on it, but I do think that syntax for packed structs should be standardized. IMO, so should syntax for inline assembly (both as optional features). These are already common extensions; this is exactly what they should standardize. The additions of "typeof" and #embed are also good examples of this (they had been talking about adding #embed since 1995 [1]).

As for vector instructions, I'm unsure how it could be implemented in a standard way, but I'm not against it. Maybe something like this [2], but with the syntax changed for C instead of C++.

[1]: https://groups.google.com/g/comp.std.c/c/zWFEXDvyTwM

[2]: https://github.com/VcDevel/std-simd

Interesting, thanks for sharing :)

At the time we open-sourced Highway, the standardization process had already started and there were some discussions.

I'm curious why stdlib is the only path you see to default? Compare the activity level of https://github.com/VcDevel/std-simd vs https://github.com/google/highway. As to open-source usage, after years of std::experimental, I see <200 search hits [1], vs >400 for Highway [2], even after excluding several library users.

But that aside, I'm not convinced standardization is the best path for a SIMD library. We and external users extend Highway on a weekly basis as new use cases arise. What if we deferred those changes to 3-monthly meetings, or had to wait for one meeting per WD, CD, (FCD), DIS, (FDIS) stage before it's standardized? Standardization seems more useful for rarely-changing things.

1: https://sourcegraph.com/search?q=context:global+std::experim...

2: https://sourcegraph.com/search?q=context:global+HWY_NAMESPAC...

std-simd - 451 GH stars

Bad news. For SIMD there are not cross-platform intrinsics. Intel intrinsics map directly to SSE/AVX instructions and ARM intrinsics map directly to NEON instructions.

For cross-platform, your best bet is probably https://github.com/VcDevel/std-simd

There's https://eigen.tuxfamily.org/index.php?title=Main_Page But, it's tremendously complicated for anything other than large-scale linear algebra.

And, there's https://github.com/microsoft/DirectXMath But, it has obvious biases :P

But after I worked with auto-vectorization(I wrote about that in part 2), I decided to switch and try myself by adding intrinsics if I was able. You can track my progress here:https://github.com/VcDevel/std-simd/pull/35

STD-SIMD it's almost the same project I was working, but a bit advance https://github.com/VcDevel/std-simd.

If you are worried about Intel vs Arm vs whatever, use https://github.com/VcDevel/std-simd

or https://github.com/KhronosGroup/Vulkan-Hpp which help quite a bit. Or https://github.com/VcDevel/std-simd.

If you want GUIs, same, you have at least (but not only) Qt or WxWidgets.

Want to interface scripting? Pybind11, Boost.Python, WrenBind17 for Wren, Sol2 for Lua... and all things that interface to C work also if you feel brave...

I really think that when it is about getting the job done... C++ goes a long way towards the task.

This is my 20 year experience of C++, almost 13 of those years professionally. Now, back to read the paper. :)

... I just checked your link and wouldn't say that any of these languages have SIMD more than C++ has it currently -

- Java: incubation stage (how is that different from https://github.com/VcDevel/std-simd). Also Java is only getting it soonish for... amd64 and aarch64 ??

I've decided to switch to something better, and after a few hours of searching, I found this repository: NSIMD https://github.com/agenium-scale/nsimd FastDifferentialCoding https://github.com/lemire/FastDifferentialCoding VS https://github.com/VcDevel/Vc XSIMD https://github.com/xtensor-stack/xsimd

> - Waiting for Cross-Platform standardized SIMD vector datatypes

which language has standardized SIMD vector datatypes ? most languages don't even have any ability to express SIMD while in C++ I can just use Vc (https://github.com/VcDevel/Vc), nsimd (https://github.com/agenium-scale/nsimd) or one of the other ton of alternatives, and have stuff that JustWorksTM on more architectures than most languages even support

- Using nonstandard extensions, libraries or home-baked solutions to run computations in parallel on many cores or on different processors than the CPU

what are the other native languages with a standardized memory model for atomics ? and, what's the problem with using libraries ? it's not like you're going to use C# or Java's built-in threadpools if you are doing any serious work, no ? Do they even have something as easy to use as https://github.com/taskflow/taskflow ?

- Debugging cross-platform code using couts, cerrs and printfs

because people never use console.log in JS or System.println in C# maybe ?

- Forced to use boost for even quite elementary operations on std::strings.

can you point to non-trivial java projects that do not use Apache Commons ? Also, the boost string algorithms are header-only so you will end up with exactly the same binaries that if it was in some std::string_algorithms namespace:

https://gcc.godbolt.org/z/43vKadbde