autodiff
automatic differentiation made easier for C++ (by autodiff)
| autodiff | geodesic_raytracing | |
|---|---|---|
| 7 | 18 | |
| 1,536 | 80 | |
| 1.2% | - | |
| 7.8 | 9.5 | |
| about 1 month ago | 3 days ago | |
| C++ | C++ | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
autodiff
Posts with mentions or reviews of autodiff.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-03-22.
- The Elements of Differentiable Programming
-
Astray: A performance-portable geodesic ray tracing library.
I completely agree. Specifying the metric rather than the Christoffel symbols would make it much easier for the users. Something like https://github.com/autodiff/autodiff might just work as the metric tensor is made up of primitives.
-
Point-to-Point Distance Constraint: Gradient of Forward Kinematics
Old username :D So far I have been using Eigen for linear algebra and NLOPT for optimization algorithms. I have found "autodiff" that hopefully looks easy to use: https://github.com/autodiff/autodiff
- Autodiff: Simple C++17 library for Automatic Differentiation
-
Gradients Without Backpropagation
Forward-mode differentiation is easy to implement in C++ with templates, operator overloading, and dual numbers (https://en.wikipedia.org/wiki/Automatic_differentiation#Auto...). Some libraries such as autodiff (https://github.com/autodiff/autodiff) and CppAD (https://github.com/coin-or/CppAD) use this method.
- Ensmallen: A C++ Library for Efficient Numerical Optimization
-
I am creating a fast, header-only, C++ library for control algorithms
I was thinking of adding [autodiff](https://github.com/autodiff/autodiff) in the future, mainly because it works seamlessly with *Eigen*. One big advantage would be that I could use it for AD for NonlinearSystems as well.
geodesic_raytracing
Posts with mentions or reviews of geodesic_raytracing.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-04.
- GPU accelerated raytracer that can render any analytic metric tensor
- Introducing posh: Type-Safe Graphics Programming in Rust
-
Cyberpunk 2077: Technology Preview Of New Ray Tracing: Overdrive Mode Arrives April 11th
Someone has written a geodesic ray tracer in C++.
-
A cool little blackhole simulation using raytracing and gravity simulation.
If you're ever interested in building GR sims, I've got a lot of experience here and maintain a similar tool for GR raytracing here
- Researchers suggest that wormholes may look almost identical to black holes
- Astray: A performance-portable geodesic ray tracing library.
-
Clang for Windows
This is untrue, I've shipped single executable binaries before with mingw. If you check out the latest project I've released, the only binary dependencies are libOpenCL.dll and the steam dll
- New C++ features in GCC 12
-
My GPU-accelerated raytracing renderer
I did build an implementation for a lot of this, so if you want this is probably a reasonable reference
- Best way to simulate total time dilation across a region of space.
What are some alternatives?
When comparing autodiff and geodesic_raytracing you can also consider the following projects:
CppAD - A C++ Algorithmic Differentiation Package: Home Page
cuda-samples - Samples for CUDA Developers which demonstrates features in CUDA Toolkit
FastAD - FastAD is a C++ implementation of automatic differentiation both forward and reverse mode.
Drogon-torch-serve - Serve pytorch / torch models using Drogon
MathNet - Math.NET Numerics
MKL.NET - A simple cross platform .NET API for Intel MKL
astray - A performance-portable geodesic ray tracing library.
CppRobotics - Header-only C++ library for robotics, control, and path planning algorithms. Work in progress, contributions are welcome!
papers - ISO/IEC JTC1 SC22 WG21 paper scheduling and management
PythonRobotics - Python sample codes for robotics algorithms.
AECforWebAssembly - A port of ArithmeticExpressionCompiler from x86 to WebAssembly, so that the programs written in the language can run in a browser. The compiler has been rewritten from JavaScript into C++.
autodiff vs CppAD
geodesic_raytracing vs cuda-samples
autodiff vs FastAD
geodesic_raytracing vs Drogon-torch-serve
autodiff vs MathNet
geodesic_raytracing vs FastAD
autodiff vs MKL.NET
geodesic_raytracing vs astray
autodiff vs CppRobotics
geodesic_raytracing vs papers
autodiff vs PythonRobotics
geodesic_raytracing vs AECforWebAssembly