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[](https://discord.gg/sg6BNzXuc7)
# ZLUDA
ZLUDA is a drop-in replacement for CUDA on non-NVIDIA GPU. ZLUDA allows to run unmodified CUDA applications using non-NVIDIA GPUs with near-native performance.
ZLUDA is work in progress. Follow development here and say hi on [Discord](https://discord.gg/sg6BNzXuc7). For more details see the announcement: https://vosen.github.io/ZLUDA/blog/zludas-third-life/
## Usage
**Warning**: ZLUDA is under heavy development (see news [here](https://vosen.github.io/ZLUDA/blog/zludas-third-life/)). Instructions below might not work.
### Windows
You should have the most recent ROCm installed.\
Run your application like this:
```
<ZLUDA_DIRECTORY>\zluda_with.exe -- <APPLICATION> <APPLICATIONS_ARGUMENTS>
```
### Linux
Run your application like this:
```
LD_LIBRARY_PATH=<ZLUDA_DIRECTORY> <APPLICATION> <APPLICATIONS_ARGUMENTS>
```
### MacOS
Not supported
## Building
**Warning**: ZLUDA is under heavy development (see news [here](https://vosen.github.io/ZLUDA/blog/zludas-third-life/)). Instructions below might not work.
_Note_: This repo has submodules. Make sure to recurse submodules when cloning this repo, e.g.: `git clone --recursive https://github.com/vosen/ZLUDA.git`
You should have a relatively recent version of Rust installed, then you just do:
```
cargo build --release
```
in the main directory of the project.
### Linux
If you are building on Linux you must also symlink (or rename) the ZLUDA output binaries after ZLUDA build finishes:
```
ln -s libnvcuda.so target/release/libcuda.so
ln -s libnvcuda.so target/release/libcuda.so.1
ln -s libnvml.so target/release/libnvidia-ml.so
```
## Contributing
If you want to develop ZLUDA itself, read [CONTRIBUTING.md](CONTRIBUTING.md), it contains instructions how to set up dependencies and run tests
## License
This software is dual-licensed under either the Apache 2.0 license or the MIT license. See [LICENSE-APACHE](LICENSE-APACHE) or [LICENSE-MIT](LICENSE-MIT) for details
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