HPX VS Bullet

https://github.com/STEllAR-GROUP/hpx Modern C++ concepts incorporated in a threading library. Lots of useful techniques used in there and we are trying to keep our code base very tidy. Feel free to chime in our libera channel #ste||ar if you have any questions.

https://github.com/STEllAR-GROUP/hpx Welcoming community + we have been part of GSoC for 4-5 years now so feel free to apply there when it opens ;)

You definitely do not want to learn Boost, trust me. The cudatoolkit is fine, HPX is great, so are Dask, and Ray. I do not recommend MPI unless those computers you have use InfiniBand.

I found this interesting library that might fit your goal.

I personally like the ideas in Parallelism v2 TS, which is available in for libstdc++ 11 onwards. The reference implementation is a library named Vc (afaik Vc is the most popular SIMD library for C++), and this has also been implemented in recent versions of HPX.

I am aware of DAGs of task based threading library like Taskflow and HPX however the benefit they have is not obvious to me, as the following sequential section depends on the parallel part being completed fully. If you want to suggest elaboration on the benefits of this approach would be welcome.

Github: https://github.com/STEllAR-GROUP/hpx

We're working on something similar, but based on sender/receiver in HPX (a lightweight threading runtime) and DLA-Future (distributed linear algebra currently based on (HPX) futures; based on sender/receiver in the future). With senders-as-awaitables this would also get you coroutine support for asynchronous MPI calls for free. We don't have that yet, but it's planned. In the meantime libunifex should be able to fill in the gaps.

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)...

I suspect most C++ physics libraries like Box2D (https://github.com/erincatto/box2d) or Bullet3 (https://github.com/bulletphysics/bullet3) could really benefit a lot from SIMD.

No, they replaced Bullet with Jolt. That is considerably more than "some adjustment", regardless of what you think of the result.

Vulkan graphics via Intel GVK, and physics via Bullet

The first two have a bunch of great examples, and I’m tying them together by refactoring some of the THREE examples to fit the ECS paradigm defined in AFrame. then upping the ante by adding physics using AMMO, which is more challenging since it’s only a partial implementation of Bullet, and already poorly documented (yet popular) physics engine.

Plus, SM uses a system called bullet physics, I imagine this would be rather complex to rework into a modern engine such as Unreal or Unity (after all, the majority of performance issues come from the physics engine rather than the graphics engine)

The physics in HDT-SMP are actually being calculated outside of Skyrim's engine with Bullet, an open-source physics engine. So this isn't some limitation of Skyrim's engine.