fast_float VS rapidobj

> Google put in significant engineering effort into "Ryu", a parsing library for double-precision floating point numbers: https://github.com/ulfjack/ryu

It's not a parsing library, but a printing one, i.e., double -> string. https://github.com/fastfloat/fast_float is a parsing library, i.e., string -> double, not by Google though, but was indeed motivated by parsing JSON fast https://lemire.me/blog/2020/03/10/fast-float-parsing-in-prac...

For those that don't know, gcc 12.x updated its float parsing logic to something similar to fast_float and it's about 1/6 of the cost presented here (sub 100 in the graph presented here). Strongly suggest using that library or upgrading the compiler if you need the performance.

This makes sense for integers but betware floating point from_chars - libc++ still doesn't implement it and libstdc++ implements it by wrapping locale-dependent libc functions which involves temporarily changing the thread locale and possibly memory allocation to make the passed string 0-terminated. IMO libstdc++'s checkbox "solution" is worse than not implementing it at all - user's are better off using Lemire's API-compatible fast_float implementation [0].

[0] https://github.com/fastfloat/fast_float

I'm a bit stuck on how to do the same thing in c++, due to containers only having a single type. The very inefficient way I'm currently doing it is by passing a program as a vector of strings, and then converting the string constants to doubles with the fast_float library.

Just above this comment is a merged PR, which references fast_float library: https://github.com/fastfloat/fast_float

Daniel Lemire @lemire (creator of the algorithm, author of the C++ implementation, and provided constant feedback to help guide the PR).

And out of 6,000 lines in the file, at least 3000 are other people's code: earcut for polygon triangulation and fast_float because .obj files typically contain a lot of floating point numbers so it's important to parse them quickly.

How this compares to https://github.com/fastfloat/fast_float ?

I tried to compare it against Daniel Lemire's excellent fast_float library. Fast float took about 180ms for the same program, and all I did was change "std" namespace prefix to "fast_float". It's a factor of 12 difference, at least my machine. I tried MSVC next, and it is a lot better, but it is still ~4 times slower than fast float. AFAIK, clang currently does not implement the feature at all.

If you don't mind a 3rd party lib until your stdlib updates, https://github.com/fastfloat/fast_float is best-in-class.

I wrote a rapidobj library for parsing Wavefront .obj files. It's an old text format for 3D data. This library was optimised to quickly process large files (see benchmarks); it can parse millions and even tens of millions of triangles per second.

I just released rapidobj v1.0. It's a fast .obj file parser. May be useful to those who need to quickly load large .obj models (of course, you will still need to transform the data into something that's GPU friendly). Third party benchmarks: https://aras-p.info/blog/2022/05/14/comparing-obj-parse-libraries/