CGal VS eigen

But I doubt any of this will ever run on the GPU... Multi-threading on the other hand, is already implemented and it works on the Gamma side, but I had to switch it off by default because CGAL doesn't seem to be there yet (see here for more). It does mostly work though, at least for the polyhedral operation which is what matters, although it may not be the great speed-up you expect it to be.

git clone https://github.com/CGAL/cgal.git

Is Eigen still alive? There's been no release in 3 years, and no news about it: https://gitlab.com/libeigen/eigen/-/issues/2699

I was curious about these libraries a few weeks ago and did some searching. Is there one that's got a clearly dominating set of users or contributors?

I don't know what a good way to compare these might be, other than perhaps activity/contributor count.

[1] https://github.com/simd-everywhere/simde

[2] https://github.com/ermig1979/Simd

[3] https://github.com/google/highway

[4] https://gitlab.com/libeigen/eigen

[5] https://github.com/shibatch/sleef

I am trying to include Eigen in my project via FetchContent. They define/assume-defined PROJECT_IS_TOP_LEVEL on line 19 and, among other locations, on line 607 in their top level list file.

Eigen is a header-only library, thus simply cloning it from the official repository into the FOGGDD folder should be enough.

math library because you should never implement a math library yourself, and you probably want somethign more focused on performance than STL. GLM may work if you just need basic vector support. Eigen may help for a more physics heavy game. But I'd probably find something in-between those two

cmake_minimum_required(VERSION 3.15) project(app) include(FetchContent) FetchContent_Declare(Eigen3 URL https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4.0.tar.gz) FetchContent_MakeAvailable(Eigen3) add_executable(app main.cpp) target_link_libraries(app Eigen3::Eigen)

Today was very easy to do with Eigen