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[Docs]: https://docs.rs/krnl
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# krnl
Safe, portable, high performance compute (GPGPU) kernels.
Developed for [autograph](https://github.com/charles-r-earp/autograph).
- Similar functionality to CUDA and OpenCL.
- Supports GPU's and other Vulkan 1.2 capable devices.
- MacOS / iOS supported via [MoltenVK](https://github.com/KhronosGroup/MoltenVK).
- Kernels are written inline, entirely in Rust.
- Simple iterator patterns can be implemented without unsafe.
- Supports inline [SPIR-V](https://www.khronos.org/spir) assembly.
- DebugPrintf integration, generates backtraces for panics.
- Buffers on the host can be accessed natively as Vecs and slices.
# krnlc
Kernel compiler for krnl.
- Built on [spirv-builder](https://github.com/EmbarkStudios/rust-gpu/tree/main/crates/spirv-builder).
- Supports dependencies defined in Cargo.toml.
- Uses [spirv-tools](https://github.com/EmbarkStudios/spirv-tools-rs) to validate and optimize.
- Compiles to "krnl-cache.rs", so the crate will build on stable Rust.
See the docs for installation and usage instructions.
# Installing
For device functionality (kernels), install [Vulkan](https://www.vulkan.org) for your platform.
- For development, it's recomended to install the [LunarG Vulkan SDK](https://www.lunarg.com/vulkan-sdk/), which includes additional tools:
- vulkaninfo
- Validation layers
- DebugPrintf
- spirv-tools
- This is used by krnlc for spirv validation and optimization.
- krnlc builds by default without needing spirv-tools to be installed.
## Test
- Check that `vulkaninfo --summary` shows your devices.
- Instance version should be >= 1.2.
- Alternatively, check that `cargo test --test integration_tests -- --exact none` shows your devices.
- You can run all the tests with `cargo test --all-features`.
# Getting Started
See the [docs](https://docs.rs/krnl) or build them locally with `cargo doc --all-features`.
# Example
```rust
use krnl::{
macros::module,
anyhow::Result,
device::Device,
buffer::{Buffer, Slice, SliceMut},
};
#[module]
mod kernels {
#[cfg(not(target_arch = "spirv"))]
use krnl::krnl_core;
use krnl_core::macros::kernel;
pub fn saxpy_impl(alpha: f32, x: f32, y: &mut f32) {
*y += alpha * x;
}
// Item kernels for iterator patterns.
#[kernel]
pub fn saxpy(alpha: f32, #[item] x: f32, #[item] y: &mut f32) {
saxpy_impl(alpha, x, y);
}
// General purpose kernels like CUDA / OpenCL.
#[kernel]
pub fn saxpy_global(alpha: f32, #[global] x: Slice<f32>, #[global] y: UnsafeSlice<f32>) {
use krnl_core::buffer::UnsafeIndex;
let global_id = kernel.global_id();
if global_id < x.len().min(y.len()) {
saxpy_impl(alpha, x[global_id], unsafe { y.unsafe_index_mut(global_id) });
}
}
}
fn saxpy(alpha: f32, x: Slice<f32>, mut y: SliceMut<f32>) -> Result<()> {
if let Some((x, y)) = x.as_host_slice().zip(y.as_host_slice_mut()) {
x.iter()
.copied()
.zip(y.iter_mut())
.for_each(|(x, y)| kernels::saxpy_impl(alpha, x, y));
return Ok(());
}
if true {
kernels::saxpy::builder()?
.build(y.device())?
.dispatch(alpha, x, y)
} else {
// or
kernels::saxpy_global::builder()?
.build(y.device())?
.with_global_threads(y.len() as u32)
.dispatch(alpha, x, y)
}
}
fn main() -> Result<()> {
let x = vec![1f32];
let alpha = 2f32;
let y = vec![0f32];
let device = Device::builder().build().ok().unwrap_or(Device::host());
let x = Buffer::from(x).into_device(device.clone())?;
let mut y = Buffer::from(y).into_device(device.clone())?;
saxpy(alpha, x.as_slice(), y.as_slice_mut())?;
let y = y.into_vec()?;
println!("{y:?}");
Ok(())
}
```
# Performance
_NVIDIA GeForce GTX 1060 with Max-Q Design_
[benches/compute-benches](benches/compute-benches)
## alloc
| **`1,000,000`** | `316.90 ns` (✅ **1.00x**) | `112.84 us` (❌ _356.06x slower_) | `495.45 ns` (❌ _1.56x slower_) |
| **`10,000,000`** | `318.15 ns` (✅ **1.00x**) | `1.10 ms` (❌ _3454.98x slower_) | `506.82 ns` (❌ _1.59x slower_) |
| **`64,000,000`** | `317.56 ns` (✅ **1.00x**) | `6.31 ms` (❌ _19854.77x slower_) | `506.15 ns` (❌ _1.59x slower_) |
## upload
| **`1,000,000`** | `332.66 us` (✅ **1.00x**) | `359.18 us` (✅ **1.08x slower**) | `773.51 us` (❌ _2.33x slower_) |
| **`10,000,000`** | `4.83 ms` (✅ **1.00x**) | `3.69 ms` (✅ **1.31x faster**) | `8.76 ms` (❌ _1.81x slower_) |
| **`64,000,000`** | `25.24 ms` (✅ **1.00x**) | `24.34 ms` (✅ **1.04x faster**) | `57.02 ms` (❌ _2.26x slower_) |
## download
| **`1,000,000`** | `584.39 us` (✅ **1.00x**) | `447.38 us` (✅ **1.31x faster**) | `20.17 ms` (❌ _34.52x slower_) |
| **`10,000,000`** | `5.67 ms` (✅ **1.00x**) | `4.03 ms` (✅ **1.41x faster**) | `20.15 ms` (❌ _3.55x slower_) |
| **`64,000,000`** | `28.82 ms` (✅ **1.00x**) | `25.57 ms` (✅ **1.13x faster**) | `37.01 ms` (❌ _1.28x slower_) |
## zero
| **`1,000,000`** | `38.15 us` (✅ **1.00x**) | `25.28 us` (✅ **1.51x faster**) | `34.12 us` (✅ **1.12x faster**) |
| **`10,000,000`** | `250.90 us` (✅ **1.00x**) | `242.95 us` (✅ **1.03x faster**) | `251.86 us` (✅ **1.00x slower**) |
| **`64,000,000`** | `1.53 ms` (✅ **1.00x**) | `1.55 ms` (✅ **1.01x slower**) | `1.56 ms` (✅ **1.02x slower**) |
## saxpy
| **`1,000,000`** | `90.76 us` (✅ **1.00x**) | `81.16 us` (✅ **1.12x faster**) | `88.94 us` (✅ **1.02x faster**) |
| **`10,000,000`** | `746.92 us` (✅ **1.00x**) | `770.03 us` (✅ **1.03x slower**) | `779.90 us` (✅ **1.04x slower**) |
| **`64,000,000`** | `4.71 ms` (✅ **1.00x**) | `4.90 ms` (✅ **1.04x slower**) | `4.91 ms` (✅ **1.04x slower**) |
# Recent Changes
See [Releases.md](https://github.com/charles-r-earp/krnl/blob/main/Releases.md)
# License
Dual-licensed to be compatible with the Rust project.
Licensed under the Apache License, Version 2.0 http://www.apache.org/licenses/LICENSE-2.0 or the MIT license http://opensource.org/licenses/MIT, at your option. This file may not be copied, modified, or distributed except according to those terms.
# 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.