extern crate alloc;
#[macro_use]
extern crate derive_new;
pub mod frontend;
pub mod io;
pub mod post_processing;
pub use cubecl_common::future;
use cubecl_ir::LineSize;
use cubecl_runtime::client::ComputeClient;
pub use cubecl_runtime::memory_management::MemoryConfiguration;
use cubecl_runtime::server::CubeCountSelection;
pub use frontend::cmma;
pub use cubecl_ir as ir;
pub mod codegen;
pub mod compute;
pub mod prelude;
mod pod;
pub use codegen::*;
pub use cubecl_runtime::runtime::*;
pub use pod::*;
pub use cubecl_macros::*;
pub use cubecl_runtime::benchmark;
pub use cubecl_runtime::client;
pub use cubecl_runtime::compiler::{CompilationError, Compiler, CubeTask};
pub use cubecl_runtime::memory_management::MemoryUsage;
pub use cubecl_runtime::server;
pub use cubecl_runtime::tune;
use frontend::LaunchArg;
pub use cubecl_common::*;
pub use prelude::CubeCount;
pub use prelude::{CubeDim, ExecutionMode};
pub use num_traits;
mod id;
pub use id::*;
pub fn calculate_cube_count_elemwise<R: Runtime>(
client: &ComputeClient<R>,
num_elems: usize,
cube_dim: CubeDim,
) -> CubeCount {
let num_cubes = num_elems.div_ceil(cube_dim.num_elems() as usize);
CubeCountSelection::new(client, num_cubes as u32).cube_count()
}
pub fn tensor_vectorization_factor(
factors: &[LineSize],
shape: &[usize],
strides: &[usize],
dim: usize,
) -> LineSize {
tensor_line_size_parallel(factors.iter().cloned(), shape, strides, dim)
}
pub fn tensor_line_size(
factors: &[LineSize],
shape: &[usize],
strides: &[usize],
dim: usize,
) -> LineSize {
tensor_line_size_parallel(factors.iter().cloned(), shape, strides, dim)
}
#[derive(Debug, Clone)]
pub enum LineSizeError {
AxisOutOfBounds,
StrideMismatch,
NoValidLineSize,
}
pub fn tensor_line_size_parallel(
supported_line_sizes: impl Iterator<Item = LineSize>,
shape: &[usize],
strides: &[usize],
axis: usize,
) -> LineSize {
try_tensor_line_size_parallel(supported_line_sizes, shape, strides, axis).unwrap_or(1)
}
pub fn try_tensor_line_size_parallel(
supported_line_sizes: impl Iterator<Item = LineSize>,
shape: &[usize],
strides: &[usize],
axis: usize,
) -> Result<LineSize, LineSizeError> {
let stride = strides.get(axis).ok_or(LineSizeError::AxisOutOfBounds)?;
if *stride != 1 {
return Err(LineSizeError::StrideMismatch);
}
let axis_shape = shape.get(axis).ok_or(LineSizeError::AxisOutOfBounds)?;
let next_stride = *strides
.iter()
.filter(|&&stride| stride > 1)
.min()
.unwrap_or(&0);
supported_line_sizes
.filter(|&line_size| axis_shape % line_size == 0 && next_stride % line_size == 0)
.max()
.ok_or(LineSizeError::NoValidLineSize)
}
pub fn tensor_line_size_perpendicular(
supported_line_sizes: impl Iterator<Item = LineSize>,
shape: &[usize],
strides: &[usize],
axis: usize,
) -> LineSize {
try_tensor_line_size_perpendicular(supported_line_sizes, shape, strides, axis).unwrap_or(1)
}
pub fn try_tensor_line_size_perpendicular(
supported_line_sizes: impl Iterator<Item = LineSize>,
shape: &[usize],
strides: &[usize],
axis: usize,
) -> Result<LineSize, LineSizeError> {
let axis_stride = strides.get(axis).ok_or(LineSizeError::AxisOutOfBounds)?;
let prod_shape_axes_smaller_strides = strides
.iter()
.zip(shape.iter())
.filter(|(stride, _)| **stride < *axis_stride)
.map(|(_, shape)| shape)
.product::<usize>();
if *axis_stride != prod_shape_axes_smaller_strides {
return Err(LineSizeError::StrideMismatch);
}
supported_line_sizes
.filter(|&line_size| *axis_stride % line_size == 0)
.max()
.ok_or(LineSizeError::NoValidLineSize)
}
pub type RuntimeArg<'a, T, R> = <T as LaunchArg>::RuntimeArg<'a, R>;
#[cfg(feature = "export_tests")]
pub mod runtime_tests;