oneDNN
Box2D
oneDNN | Box2D | |
---|---|---|
5 | 35 | |
3,461 | 7,291 | |
1.7% | - | |
10.0 | 0.0 | |
7 days ago | about 2 months ago | |
C++ | C++ | |
Apache License 2.0 | MIT License |
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oneDNN
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Blaze: A High Performance C++ Math library
If you are talking about non-small matrix multiplication in MKL, is now in opensource as a part of oneDNN. It literally has exactly the same code, as in MKL (you can see this by inspecting constants or doing high-precision benchmarks).
For small matmul there is libxsmm. It may take tremendous efforts make something faster than oneDNN and libxsmm, as jit-based approach of https://github.com/oneapi-src/oneDNN/blob/main/src/gpu/jit/g... is too flexible: if someone finds a better sequence, oneDNN can reuse it without major change of design.
But MKL is not limited to matmul, I understand it...
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Arc & Deep Learning Frameworks
For completeness, it looks like this question was posted to the oneDNN GitHub repo and the response was to stay tune for updates.
- Keeping POWER relevant in the open source world
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Intel oneDNN 2.5 released with experimental RISC-V support
From the release note of oneDNN v2.5:
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Is gpu hardware tied to cpu ISA ?
Intel are trying to support their oneAPI compute framework on Arm and IBM POWER and z/Architecture (s390x) but since they ever released only a single discrete GPU with the Xe architecture it's unclear whether they'll support Xe GPU compute on e.g. ARM https://github.com/oneapi-src/oneDNN
Box2D
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Blaze: A High Performance C++ Math library
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)...
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Jolt Physics raylib: trying 3D C++ Game Physics Engine
Box2D: 2D engine used in Unity and also earlier versions of Godot. Open source.
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Rust Game Physics Engines: PhysX, Rapier, XPBD & Others
Box2D GitHub repo: erincatto/box2d
- Nebula is an open-source and free-to-use modern C++ game engine
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Linear code is more readable
Why is 600 lines too long? How are you able to make that judgment call without first knowing what the algorithm is even doing? People setting arbitrary limits like this is what leads to convoluted spaghetti, instead of just taking things on a case by case basis. Here’s a function from the Box2D code running a particularly complex algorithm for solving contact velocities https://github.com/erincatto/box2d/blob/411acc32eb6d4f2e96fc... .
It’s 310 lines long. It reads very well, and it looks very maintainable. It has very clear comments explaining the reasoning behind the harder parts of the code. Would you reject this code because it’s pretty long? I wouldn’t.
There is no such thing as too long or too short. There’s overengineered and there’s underengineered and there’s a sweet spot in the middle that has the perfect amount of engineering with the least amount of complexity (preferably no additional complexity than the original problem warranted). Sometimes, the problem at hand is inherently a large algorithm and requires many lines of code. Don’t split it up! It just makes it harder for future maintainers who now have to figure out if the additional functions are actually being used elsewhere or if they’re just there to make the code “pretty”.
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How would you implement a simple collision system?
There is always the approach of looking at how an existing engine is implemented, such as box2d: https://github.com/erincatto/box2d
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C++23: The Next C++ Standard
TIL Box2D must not be serious code because it doesn't use copious amounts of explicit temporaries[0].
And just for the record, I'm very glad Erin Catto decided to use operator overloading in his code. It made it much easier for me to read and understand what the code was doing as opposed to it being overly verbose and noisy.
[0]: https://github.com/erincatto/box2d/blob/main/src/collision/b...
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Make a game engine in C++
For Physics Box2d can be used as a simple starting point.
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Does anyone know any good open source project to optimize?
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.
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what to start learning
for 2D physics have a look at Box2D it's amazing https://box2d.org/
What are some alternatives?
oneMKL - oneAPI Math Kernel Library (oneMKL) Interfaces
Bullet - Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
CTranslate2 - Fast inference engine for Transformer models
Chipmunk - A fast and lightweight 2D game physics library.
oneDPL - oneAPI DPC++ Library (oneDPL) https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/dpc-library.html
raylib - A simple and easy-to-use library to enjoy videogames programming
highway - Highway - A Modern Javascript Transitions Manager
LiquidFun - 2D physics engine for games
asmjit - Low-latency machine code generation
PhysX - NVIDIA PhysX SDK
librealsense - Intel® RealSense™ SDK
box2d-lite - A small 2D physics engine