async-cuda
Asynchronous CUDA for Rust.
[![version](https://img.shields.io/crates/v/async-cuda)](https://crates.io/crates/async-cuda)
[![license](https://img.shields.io/crates/l/async-cuda)](#license)
[![docs](https://img.shields.io/docsrs/async-cuda)](https://docs.rs/async-cuda)
## ℹ️ Introduction
`async-cuda` is an experimental library for interacting with the GPU asynchronously. Since the GPU
is just another I/O device (from the point of view of your program), the async model actually fits
surprisingly well. The way it is implemented in `async-cuda` is that all operations are scheduled on
a single runtime thread that drives the GPU. The interface of this library enforces that
synchronization happens when it is necessary (and synchronization itself is also asynchronous).
On top of common CUDA primitives, this library also includes async wrappers for
[NVIDIA's NPP library](https://developer.nvidia.com/npp).
The async wrappers for TensorRT have been moved to a separate repository here:
[`async-tensorrt`](https://github.com/oddity-ai/async-tensorrt).
## 🛠 S️️tatus
This project is still a work-in-progress, and will contain bugs. Some parts of the API have not
been flushed out yet. Use with caution.
## 📦 Setup
Make sure you have the necessary dependencies installed:
* CUDA toolkit 11 or later.
Then, add the following to your dependencies in `Cargo.toml`:
```toml
async-cuda = "0.6"
```
To enable the NPP functions:
```toml
async-cuda = { version = "0.6", features = ["npp"] }
```
## ⚠️ Safety warning
This crate is **intentionally unsafe**. Due to the limitations of how async Rust currently works,
usage of the async interface of this crate can cause undefined behavior in some rare cases. It is up
to the user of this crate to prevent this from happening by following these rules:
* No futures produced by functions in this crate may be leaked (either by `std::mem::forget` or
otherwise).
* Use a well-behaved runtime (one that will not forget your future) like Tokio or async-std.
Internally, the `Future` type in this crate schedules a CUDA call on a separate runtime thread. To
make the API as ergonomic as possible, the lifetime bounds of the closure (that is sent to the
runtime) are tied to the future object. To enforce this bound, the future will block and wait if it
is dropped. This mechanism relies on the future being driven to completion, and not forgotten. This
is not necessarily guaranteed. Unsafety may arise if either the runtime gives up on or forgets the
future, or the caller manually polls the future, then forgets it.
## License
Licensed under either of
* Apache License, Version 2.0
([LICENSE-APACHE](LICENSE-APACHE) or http://www.apache.org/licenses/LICENSE-2.0)
* MIT license
([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT)
at your option.
## Contribution
Unless you explicitly state otherwise, any contribution intentionally submitted
for inclusion in the work by you, as defined in the Apache-2.0 license, shall be
dual licensed as above, without any additional terms or conditions.