use core::marker::PhantomData;
use baracuda_cutlass::{Error, Result};
use baracuda_driver::Stream;
use baracuda_kernels_types::{
ArchSku, AttentionKind, BackendKind, Element, ElementKind, KernelSku, MathPrecision,
OpCategory, PlanPreference, PrecisionGuarantee, TensorMut, TensorRef, Workspace,
};
#[derive(Copy, Clone, Debug)]
pub struct CascadeAttentionDescriptor {
pub seq_len: i32,
pub num_heads: i32,
pub head_dim: i32,
pub element: ElementKind,
}
pub struct CascadeAttentionArgs<'a, T: Element> {
pub v: TensorMut<'a, T, 3>,
pub s: TensorMut<'a, f32, 2>,
pub v_other: TensorRef<'a, T, 3>,
pub s_other: TensorRef<'a, f32, 2>,
}
pub struct CascadeAttentionPlan<T: Element> {
desc: CascadeAttentionDescriptor,
sku: KernelSku,
_marker: PhantomData<T>,
}
impl<T: Element> CascadeAttentionPlan<T> {
pub fn select(
_stream: &Stream,
desc: &CascadeAttentionDescriptor,
_pref: PlanPreference,
) -> Result<Self> {
if desc.element != T::KIND {
return Err(Error::Unsupported(
"CascadeAttentionPlan: descriptor element != T",
));
}
if desc.seq_len <= 0 || desc.num_heads <= 0 {
return Err(Error::InvalidProblem(
"CascadeAttentionPlan: extents must be positive",
));
}
if !matches!(desc.head_dim, 64 | 128 | 256) {
return Err(Error::Unsupported(
"CascadeAttentionPlan: head_dim must be 64, 128, or 256",
));
}
if !matches!(T::KIND, ElementKind::F16 | ElementKind::Bf16 | ElementKind::F32) {
return Err(Error::Unsupported(
"CascadeAttentionPlan: element type must be f16, bf16, or f32",
));
}
let precision_guarantee = PrecisionGuarantee {
math_precision: MathPrecision::F32,
accumulator: ElementKind::F32,
bit_stable_on_same_hardware: true,
deterministic: true,
};
let sku = KernelSku {
category: OpCategory::Attention,
op: AttentionKind::PagedAttention as u16,
element: T::KIND,
aux_element: None,
layout: None,
epilogue: None,
arch: ArchSku::Sm80,
backend: BackendKind::FlashInfer,
precision_guarantee,
};
Ok(Self {
desc: *desc,
sku,
_marker: PhantomData,
})
}
pub fn can_implement(&self, args: &CascadeAttentionArgs<'_, T>) -> Result<()> {
let v_shape = [self.desc.seq_len, self.desc.num_heads, self.desc.head_dim];
let s_shape = [self.desc.seq_len, self.desc.num_heads];
if args.v.shape != v_shape || args.v_other.shape != v_shape {
return Err(Error::InvalidProblem(
"CascadeAttentionPlan: v / v_other shape mismatch",
));
}
if args.s.shape != s_shape || args.s_other.shape != s_shape {
return Err(Error::InvalidProblem(
"CascadeAttentionPlan: s / s_other shape mismatch",
));
}
if !args.v.is_contiguous()
|| !args.s.is_contiguous()
|| !args.v_other.is_contiguous()
|| !args.s_other.is_contiguous()
{
return Err(Error::Unsupported(
"CascadeAttentionPlan: tensors must be contiguous (Tier 1)",
));
}
Ok(())
}
#[inline]
pub fn workspace_size(&self) -> usize {
0
}
#[inline]
pub fn sku(&self) -> KernelSku {
self.sku
}
#[inline]
pub fn precision_guarantee(&self) -> PrecisionGuarantee {
self.sku.precision_guarantee
}
pub fn run(
&self,
stream: &Stream,
_workspace: Workspace<'_>,
args: CascadeAttentionArgs<'_, T>,
) -> Result<()> {
self.can_implement(&args)?;
#[cfg(not(feature = "flashinfer"))]
{
let _ = (stream, &args);
Err(Error::Unsupported(
"CascadeAttentionPlan: `flashinfer` cargo feature is not enabled",
))
}
#[cfg(feature = "flashinfer")]
{
let stream_ptr = stream.as_raw() as *mut c_void;
let v_ptr = args.v.data.as_raw().0 as *mut c_void;
let s_ptr = args.s.data.as_raw().0 as *mut c_void;
let v_other_ptr = args.v_other.data.as_raw().0 as *const c_void;
let s_other_ptr = args.s_other.data.as_raw().0 as *const c_void;
let status = match T::KIND {
ElementKind::F16 => unsafe {
baracuda_kernels_sys::baracuda_kernels_flashinfer_merge_state_in_place_f16_run(
self.desc.seq_len, self.desc.num_heads, self.desc.head_dim,
v_ptr, s_ptr, v_other_ptr, s_other_ptr, stream_ptr,
)
},
ElementKind::Bf16 => unsafe {
baracuda_kernels_sys::baracuda_kernels_flashinfer_merge_state_in_place_bf16_run(
self.desc.seq_len, self.desc.num_heads, self.desc.head_dim,
v_ptr, s_ptr, v_other_ptr, s_other_ptr, stream_ptr,
)
},
ElementKind::F32 => unsafe {
baracuda_kernels_sys::baracuda_kernels_flashinfer_merge_state_in_place_f32_run(
self.desc.seq_len, self.desc.num_heads, self.desc.head_dim,
v_ptr, s_ptr, v_other_ptr, s_other_ptr, stream_ptr,
)
},
_ => {
return Err(Error::Unsupported(
"CascadeAttentionPlan::run reached an unimplemented dtype",
));
}
};
map_status(status)
}
}
}
#[derive(Copy, Clone, Debug)]
pub struct CascadeMergeStatesDescriptor {
pub num_index_sets: i32,
pub seq_len: i32,
pub num_heads: i32,
pub head_dim: i32,
pub element: ElementKind,
}
pub struct CascadeMergeStatesArgs<'a, T: Element> {
pub v: TensorRef<'a, T, 4>,
pub s: TensorRef<'a, f32, 3>,
pub v_merged: TensorMut<'a, T, 3>,
pub s_merged: TensorMut<'a, f32, 2>,
}
pub struct CascadeMergeStatesPlan<T: Element> {
desc: CascadeMergeStatesDescriptor,
sku: KernelSku,
_marker: PhantomData<T>,
}
impl<T: Element> CascadeMergeStatesPlan<T> {
pub fn select(
_stream: &Stream,
desc: &CascadeMergeStatesDescriptor,
_pref: PlanPreference,
) -> Result<Self> {
if desc.element != T::KIND {
return Err(Error::Unsupported(
"CascadeMergeStatesPlan: descriptor element != T",
));
}
if desc.num_index_sets <= 0 || desc.seq_len <= 0 || desc.num_heads <= 0 {
return Err(Error::InvalidProblem(
"CascadeMergeStatesPlan: extents must be positive",
));
}
if !matches!(desc.head_dim, 64 | 128 | 256) {
return Err(Error::Unsupported(
"CascadeMergeStatesPlan: head_dim must be 64, 128, or 256",
));
}
if !matches!(T::KIND, ElementKind::F16 | ElementKind::Bf16 | ElementKind::F32) {
return Err(Error::Unsupported(
"CascadeMergeStatesPlan: element type must be f16, bf16, or f32",
));
}
let precision_guarantee = PrecisionGuarantee {
math_precision: MathPrecision::F32,
accumulator: ElementKind::F32,
bit_stable_on_same_hardware: true,
deterministic: true,
};
let sku = KernelSku {
category: OpCategory::Attention,
op: AttentionKind::PagedAttention as u16,
element: T::KIND,
aux_element: None,
layout: None,
epilogue: None,
arch: ArchSku::Sm80,
backend: BackendKind::FlashInfer,
precision_guarantee,
};
Ok(Self {
desc: *desc,
sku,
_marker: PhantomData,
})
}
pub fn can_implement(&self, args: &CascadeMergeStatesArgs<'_, T>) -> Result<()> {
let v_shape = [
self.desc.seq_len,
self.desc.num_index_sets,
self.desc.num_heads,
self.desc.head_dim,
];
let s_shape = [self.desc.seq_len, self.desc.num_index_sets, self.desc.num_heads];
let v_merged_shape = [self.desc.seq_len, self.desc.num_heads, self.desc.head_dim];
let s_merged_shape = [self.desc.seq_len, self.desc.num_heads];
if args.v.shape != v_shape {
return Err(Error::InvalidProblem("CascadeMergeStatesPlan: v shape mismatch"));
}
if args.s.shape != s_shape {
return Err(Error::InvalidProblem("CascadeMergeStatesPlan: s shape mismatch"));
}
if args.v_merged.shape != v_merged_shape {
return Err(Error::InvalidProblem(
"CascadeMergeStatesPlan: v_merged shape mismatch",
));
}
if args.s_merged.shape != s_merged_shape {
return Err(Error::InvalidProblem(
"CascadeMergeStatesPlan: s_merged shape mismatch",
));
}
if !args.v.is_contiguous()
|| !args.s.is_contiguous()
|| !args.v_merged.is_contiguous()
|| !args.s_merged.is_contiguous()
{
return Err(Error::Unsupported(
"CascadeMergeStatesPlan: tensors must be contiguous (Tier 1)",
));
}
Ok(())
}
#[inline]
pub fn workspace_size(&self) -> usize {
0
}
#[inline]
pub fn sku(&self) -> KernelSku {
self.sku
}
#[inline]
pub fn precision_guarantee(&self) -> PrecisionGuarantee {
self.sku.precision_guarantee
}
pub fn run(
&self,
stream: &Stream,
_workspace: Workspace<'_>,
args: CascadeMergeStatesArgs<'_, T>,
) -> Result<()> {
self.can_implement(&args)?;
#[cfg(not(feature = "flashinfer"))]
{
let _ = (stream, &args);
Err(Error::Unsupported(
"CascadeMergeStatesPlan: `flashinfer` cargo feature is not enabled",
))
}
#[cfg(feature = "flashinfer")]
{
let stream_ptr = stream.as_raw() as *mut c_void;
let v_ptr = args.v.data.as_raw().0 as *const c_void;
let s_ptr = args.s.data.as_raw().0 as *const c_void;
let v_merged_ptr = args.v_merged.data.as_raw().0 as *mut c_void;
let s_merged_ptr = args.s_merged.data.as_raw().0 as *mut c_void;
let status = match T::KIND {
ElementKind::F16 => unsafe {
baracuda_kernels_sys::baracuda_kernels_flashinfer_merge_states_f16_run(
self.desc.num_index_sets, self.desc.seq_len, self.desc.num_heads,
self.desc.head_dim, v_ptr, s_ptr, v_merged_ptr, s_merged_ptr, stream_ptr,
)
},
ElementKind::Bf16 => unsafe {
baracuda_kernels_sys::baracuda_kernels_flashinfer_merge_states_bf16_run(
self.desc.num_index_sets, self.desc.seq_len, self.desc.num_heads,
self.desc.head_dim, v_ptr, s_ptr, v_merged_ptr, s_merged_ptr, stream_ptr,
)
},
ElementKind::F32 => unsafe {
baracuda_kernels_sys::baracuda_kernels_flashinfer_merge_states_f32_run(
self.desc.num_index_sets, self.desc.seq_len, self.desc.num_heads,
self.desc.head_dim, v_ptr, s_ptr, v_merged_ptr, s_merged_ptr, stream_ptr,
)
},
_ => {
return Err(Error::Unsupported(
"CascadeMergeStatesPlan::run reached an unimplemented dtype",
));
}
};
map_status(status)
}
}
}