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https://github.com/sunsided/rust-arrayfire-experiments
Toying around with ArrayFire in Rust
https://github.com/sunsided/rust-arrayfire-experiments
arrayfire conways-game-of-life cuda gpgpu gpu-acceleration gpu-computing opencl rust
Last synced: about 2 months ago
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Toying around with ArrayFire in Rust
- Host: GitHub
- URL: https://github.com/sunsided/rust-arrayfire-experiments
- Owner: sunsided
- Created: 2020-09-04T13:17:59.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-02-03T17:34:54.000Z (about 3 years ago)
- Last Synced: 2024-11-09T08:16:00.909Z (3 months ago)
- Topics: arrayfire, conways-game-of-life, cuda, gpgpu, gpu-acceleration, gpu-computing, opencl, rust
- Language: Rust
- Homepage:
- Size: 69.3 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# GPGPU Experiments in Rust with ArrayFire
Toying around with / getting to know [arrayfire-rust](https://github.com/arrayfire/arrayfire-rust).
Don't expect anything crazy here. 🙌
## Example applications
- [conway.rs](src/conway.rs): GPU-enabled [Conway's Game of Life](https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life) through
kernel convolutions, taken from the `arrayfire-rust` examples and spiced up for readability and understandability.
Uses ArrayFire's graphics module to provide a window. See [The Game of Life vs. Convolutions](https://medium.com/@sunside/the-game-of-life-vs-convolutions-bc495c962de8) for a post on it.
```bash
cargo run
cargo run --bin conway
```
- [trivial.rs](src/trivial.rs): The simple example from the `arrayfire-rust` [README](https://github.com/arrayfire/arrayfire-rust/blob/master/README.md):
```bash
cargo run --bin trivial
```
- [white_noise.rs](src/white_noise.rs): Just white noise in a window.
```bash
cargo run --bin white-noise
```
- [half_precision.rs](src/half_precision.rs): FP16 example using [half::f16](https://docs.rs/half/1.6.0/half/).
Doesn't work on my GTX 980 Ti (Compute 5.2) with CUDA 10 / driver 450, so the CPU back-end is used instead.
```bash
cargo run --bin half-precision
```
- [adaptive_threshold.rs](src/adaptive_threshold.rs): Implements three adaptive thresholding
techniques (mean, median and min-max average) as described in [Image editing using ArrayFire: Part 3](https://arrayfire.com/image-editing-using-arrayfire-part-3-2/).
Note that the path to the image is hard-coded, so it needs to be run from the repository root.
```bash
cargo run --bin adaptive-threshold
```
- [histogram.rs](src/histogram.rs): Implements RGB histogram calculation as described in [Image editing using ArrayFire: Part 3](https://arrayfire.com/image-editing-using-arrayfire-part-3-2/).
Makes use of `slice()` and/or `index()` to obtain individual channels from an `Array`.
Note that the path to the image is hard-coded, so it needs to be run from the repository root.
```bash
cargo run --bin histogram
```
## Installing ArrayFire
From the [arrayfire-rust](https://github.com/arrayfire/arrayfire-rust) instructions:
> To use the rust bindings for ArrayFire from crates.io, the following requirements are to be met first.
>
> 1. [Download and install ArrayFire binaries](https://arrayfire.com/download) based on your operating system.
> 2. Set the evironment variable `AF_PATH` to point to ArrayFire installation root folder.
> 3. Make sure to add the path to lib files to your path environment variables.
> - On Linux: do `export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$AF_PATH/lib64`
> - On OSX: do `export DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:$AF_PATH/lib64`
> - On Windows: Add `%AF_PATH%\lib` to your PATH environment variable.
> 4. Add `arrayfire = "3.7"` to the dependencies section of your project's Cargo.toml file. Make sure
> to change the version to latest available.
>
> Once step (4) is over, you should be able to use ArrayFire in your Rust project.
## Further reading
- [The State of GPGPU in Rust](https://bheisler.github.io/post/state-of-gpgpu-in-rust/) (as of August 2018)
- [ArrayFire Examples (Part 4 of 8) - Image Processing](https://arrayfire.com/arrayfire-examples-part-4-of-8-image-processing/)
- [ArrayFire Examples (Part 5 of 8) - Machine Learning](https://arrayfire.com/arrayfire-examples-part-5-of-8-machine-learning/)
- [ArrayFire Examples (Part 7 of 8) - Partial Differential Equations](https://arrayfire.com/arrayfire-examples-part-7-of-8-pde/)
- [arrayfire/arrayfire: Machine Learning examples](https://github.com/arrayfire/arrayfire/tree/master/examples/machine_learning)
## License
- [ArrayFire](https://arrayfire.com/the-arrayfire-library/) and [arrayfire-rust](https://github.com/arrayfire/arrayfire-rust)
are licensed under a [BSD 3-Clause License](https://tldrlegal.com/license/bsd-3-clause-license-(revised)).