rsmpi
Rust-CUDA
| rsmpi | Rust-CUDA | |
|---|---|---|
| 4 | 37 | |
| 442 | 2,894 | |
| 2.9% | 2.7% | |
| 7.2 | 0.0 | |
| 11 days ago | 6 months ago | |
| Rust | Rust | |
| Apache License 2.0 | Apache License 2.0 |
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.
rsmpi
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Why should academic researchers use Rust?
Perhaps MPI?
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In which circumstances is C++ better than Rust?
- OpenMPI https://github.com/rsmpi/rsmpi and if you look at dependency you will find mpi-sys (is a rust thing but it is the current FFI part) and if go and look for it https://crates.io/crates/mpi-sys/0.2.0/dependencies sure it have it, bindgen as a dependency
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possibility of blas natively in Rust
I mean there's rsmpi (https://github.com/rsmpi/rsmpi) for MPI which now has a few active maintainers such as one who also works on PETSc and a few other HPC libraries.
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I have written a blog post about my experience using Rust for scientific numerical applications
Haven't used it myself. But this seems well maintained and very usable. https://github.com/rsmpi/rsmpi
Rust-CUDA
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[Media] Anyone try writing a ray tracer with rust? It's pretty fun!
Source code [here](https://github.com/ihawn/RTracer) if anyone is interested in taking a look or giving feedback. As a side question, does anyone have any general advise on getting GPU compute working with rust? I tried [this project](https://github.com/Rust-GPU/Rust-CUDA) but had a bunch of issues (And it doesn't look like an active repo anyways)
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Is rust or python better for Machine learning? Or is there enough decent frameworks?
You have this https://github.com/Rust-GPU/Rust-CUDA
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toolchain nightly package building issue
What I'm trying to do is check out https://github.com/Rust-GPU/Rust-CUDA for a class project.
- [Rust] État de GPGPU en 2022
- Which crate for CUDA in Rust?
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Announcing cudarc and fully GPU accelerated dfdx: ergonomic deep learning ENTIRELY in rust, now with CUDA support and tensors with mixed compile and runtime dimensions!
Be warned, NON_BLOCKING streams do not fully synchronize with sync host to device copies. They are not guaranteed to actually finish by the time they return. Meaning its possible to initiate a copy, then initiate a kernel launch, and have the copy be unfinished by the time the kernel is launched. This caused so many confusing bugs that i personally decided to stop using NON_BLOCKING altogether in rust-cuda. https://github.com/Rust-GPU/Rust-CUDA/issues/15
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In which circumstances is C++ better than Rust?
- Cuda is not doing by FFI linking, instead is compiling CUDA code natively in Rust https://github.com/Rust-GPU/Rust-CUDA and even if it not complete as the C++ SDK is more than a toy
- I learned 7 programming languages so you don't have to
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GNU Octave
Given your criteria, you might want to consider (modern) C++.
* Fast - in many cases faster than Rust, although the difference is inconsequential relative to Python-to-Rust improvement I guess.
* _Really_ utilize CUDA, OpenCL, Vulcan etc. Specifically, Rust GPU is limited in its supported features, see: https://github.com/Rust-GPU/Rust-CUDA/blob/master/guide/src/... ...
* Host-side use of CUDA is at least as nice, and probably nicer, than what you'll get with Rust. That is, provided you use my own Modern C++ wrappers for the CUDA APIs: https://github.com/eyalroz/cuda-api-wrappers/ :-) ... sorry for the shameless self-plug.
* ... which brings me to another point: Richer offering of libraries for various needs than Rust, for you to possibly utilize.
* Easier to share than Rust. A target system is less likely to have an appropriate version of Rust and the surrounding ecosystem.
There are downsides, of course, but I was just applying your criteria.
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Your average rustafarians
Technically, yes. There are crates for OpenCL and CUDA, although official ROCm support does not exist yet.
What are some alternatives?
libint - Libint: high-performance library for computing Gaussian integrals in quantum mechanics
rust-gpu - 🐉 Making Rust a first-class language and ecosystem for GPU shaders 🚧
node_crunch - Allows to distribute computations across several nodes
wgpu - A cross-platform, safe, pure-Rust graphics API.
Haskell-abinitio - contains a package in Haskell to calculate the electronic structure properties of molecules using the Hartree-Fock method
rust-ndarray - ndarray: an N-dimensional array with array views, multidimensional slicing, and efficient operations
openblas-src - Source of BLAS and LAPACK via OpenBLAS
CUDA.jl - CUDA programming in Julia.
libcint - general GTO integrals for quantum chemistry
GLSL - GLSL Shading Language Issue Tracker
intel-mkl-src - Redistribute Intel MKL as a crate
WeasyPrint - The awesome document factory