JAjanwas·Jun 9, 2023
I'm the main author of Highway, so I have some opinions :D Number of operations/platforms supported are important criteria.
A hopefully unbiased commentary:
Simde allows you to take existing nonportable intrinsics and get them to run on another platform. This is useful when you have a bunch of existing code and tight deadlines. The downside is less than optimal performance - a portable abstraction can be more efficient than forcing one platform to exactly match the semantics of another. Although a ton of effort has gone into Simde, sometimes it also resorts to autovectorization which may or may not work.
Eigen and SLEEF are mostly math-focused projects that also have a portability layer. SLEEF is designed for C and thus has type suffixes which are rather verbose, see https://github.com/shibatch/sleef/blob/master/src/libm/sleef... But it o
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ffers a complete (more so than Highway's) libm.
Eigen is similarly useful for higher-level linear algebra that you probably do not want to reimplement yourself.
However, I am skeptical of its expression template approach, in my experience one can run into trouble when the code gets complex (maybe some compiler limits are reached).
Both of them may be less useful in non-math domains, AFAIK they lack many of the specialized instructions Highway has (e.g. interleaved load/store, compress/expand, software AES/CLMUL, popcount, lzcnt, saturated add/sub, 128-bit compare/minmax, fixed-point mul). I think Eigen would struggle with dynamic dispatch because of its header-only style, and SLEEF (understandably) lacks 8/16-bit types.
Highway is used in multiple projects and because it is just a collection of wrapper functions around intrinsics, it is more predictable/reliable. For this reason it is also currently AFAIK the only solution that supports scalable vectors in SVE and RISC-V V. The main downside is that it requires C++11, and so we are unable to help projects that are C-only and cannot compile parts of their code as C++.