PhysX VS eigen

For typical game physics engines... not that much. Math libraries like Eigen or Blaze use lots of template metaprogramming techniques under the hood that can help when you're doing large batched matrix multiplications (since it can remove temporary allocations at compile-time and can also fuse operations efficiently, as well as applying various SIMD optimizations), but it doesn't really help when you need lots of small operations (with mat3 / mat4 / vec3 / quat / etc.). Typical game physics engines tend to use iterative algorithms for their solvers (Gauss-Seidel, PBD, etc...) instead of batched "matrix"-oriented ones, so you'll get less benefits out of Eigen / Blaze compared to what you typically see in deep learning / scientific computing workloads.

The codebases I've seen in many game physics engines seem to all roll their own math libraries for these stuff, or even just use SIMD (SSE / AVX) intrinsics directly. Examples: PhysX (https://github.com/NVIDIA-Omniverse/PhysX), Box2D (https://github.com/erincatto/box2d), Bullet (https://github.com/bulletphysics/bullet3)...

NVIDIA PhysX GitHub repo: NVIDIA-Omniverse/PhysX

I don’t know of any books but here is the official documentation which includes an API reference. You can also find a lot of sample code snippets and examples on their GitHub.

On the other hand, PhysX is available under the MIT License and is both heavily used in games and also well documented with tons of sample code.

The CPU implementation of PhysX is too, no reason you couldn't port that to run on AMD GPUs: https://github.com/NVIDIA-Omniverse/PhysX

The LICENSE.md file on the repo doesn't mention BSD-3-Clause at all, it's just a copywrite notice that reads more like CC-BY than a software license. That's why I said it was weird.

Very! I just picked a random file: https://github.com/NVIDIA-Omniverse/PhysX/blob/release/104.0/physx/source/physx/src/NpArticulationJointReducedCoordinate.cpp

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