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11 changes: 7 additions & 4 deletions examples/00_bmg_gemm/00_bmg_gemm.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -350,6 +350,10 @@ int main(int argc, const char** argv)
// Refer https://github.com/intel/sycl-tla/blob/main/media/docs/cpp/xe_rearchitecture.md
using GmemTiledCopyA = void; //XE_LOAD_2D<16, 32, 32>;
using GmemTiledCopyB = void; //XE_LOAD_2D_VNNI<16, 32, 32>;
using GmemTiledCopyC = XE_LOAD_2D<32, 8, 16>;
using GmemTiledCopyD = XE_STORE_2D<32, 8, 16>;



// Workgroup-level tile
using TileShape = Shape<_256, _256, _32>;
Expand All @@ -369,9 +373,8 @@ int main(int argc, const char** argv)

// For Intel BMG, PipelineStages defines how many k-blocks ahead to prefetch from A and B.
constexpr int PipelineStages = 2;
// For older version of copy/mma atom, use cutlass::gemm::MainloopIntelXeXMX16 as dispatch policy
using GEMMDispatchPolicy = cutlass::gemm::MainloopXeL1Staged<PipelineStages>;
using EpilogueDispatchPolicy = cutlass::epilogue::IntelXeXMX16;
using EpilogueDispatchPolicy = cutlass::epilogue::IntelXeL1Staged;

// This is the 'default' epilogue operation (Linear Combination) which performs everything in:
// (D = alpha * (A*B) + beta * C)
Expand All @@ -394,9 +397,9 @@ int main(int argc, const char** argv)
ElementOutput,
cutlass::gemm::TagToStrideC_t<LayoutD>, // Converts CUTLASS 2.x to CUTLASS 3.x representation
FusionCallBacks,
XE_2D_U32x8x16_LD_N, // The copy atom used to load matrix C
GmemTiledCopyC, // The copy atom used to load matrix C
void, void,
XE_2D_U32x8x16_ST_N, // The copy atom used to store matrix D
GmemTiledCopyD, // The copy atom used to store matrix D
void, void>;

// GEMM Mainloop - iteration over blocks in K dimension
Expand Down
12 changes: 11 additions & 1 deletion include/cute/atom/copy_traits_xe_2d.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -1143,12 +1143,22 @@ template <class CopyOp, class TiledMMA, class CTensor>
auto get_block_2d_copy_C(TiledMMA const& tiled_mma, CTensor const& c_tensor)
{
if constexpr (!std::is_void_v<CopyOp>) {
return make_block_2d_copy_C(CopyOp{}, tiled_mma, c_tensor);
return make_block_2d_copy_CD(CopyOp{}, tiled_mma, c_tensor);
} else {
return make_block_2d_copy_C(tiled_mma, c_tensor);
}
}

template <class CopyOp, class TiledMMA, class DTensor>
auto get_block_2d_copy_D(TiledMMA const& tiled_mma, DTensor const& d_tensor)
{
if constexpr (!std::is_void_v<CopyOp>) {
return make_block_2d_copy_CD(CopyOp{}, tiled_mma, d_tensor);
} else {
return make_block_2d_copy_D(tiled_mma, d_tensor);
}
}

//
// Display utilities
//
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -71,6 +71,7 @@ class CollectiveEpilogue {
#include "sm100_epilogue_array_tma_warpspecialized.hpp"
#if defined (SYCL_INTEL_TARGET)
#include "xe_epilogue.hpp"
#include "xe_epilogue_legacy.hpp"
#include "xe_array_epilogue.hpp"
#endif
//
Expand Down
145 changes: 82 additions & 63 deletions include/cutlass/epilogue/collective/xe_epilogue.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -68,7 +68,7 @@ template <
class CopyOpR2S_
>
class CollectiveEpilogue<
IntelXeXMX16,
IntelXeL1Staged,
CtaTileMNK_,
ElementC_,
StrideC_,
Expand All @@ -86,7 +86,7 @@ class CollectiveEpilogue<
//
// Type Aliases
//
using DispatchPolicy = IntelXeXMX16;
using DispatchPolicy = IntelXeL1Staged;
using CtaTileMNK = CtaTileMNK_;
using FusionCallbacks = FusionCallbacks_;
using ElementC = ElementC_;
Expand All @@ -102,9 +102,6 @@ class CollectiveEpilogue<
using CopyOpR2S = CopyOpR2S_;

using ThreadEpilogueOp = typename fusion::FusionCallbacksTraits<FusionCallbacks>::Operation;
using GmemTiledCopyC = conditional_t<cute::is_void_v<CopyOpG2R>, XE_2D_U32x8x16_LD_N, CopyOpG2R>;
using GmemTiledCopyD = cute::conditional_t<not cute::is_void_v<ElementD> && not cute::is_void_v<CopyOpR2G>,
CopyOpR2G, XE_2D_U32x8x16_ST_N>;
using ElementOutput = ElementD;
using ElementCompute = ElementAccumulator;

Expand All @@ -119,19 +116,10 @@ class CollectiveEpilogue<
static_assert(std::is_same_v<SmemLayoutAtomC, void>, "Copy operation to shared memory is not supported");
static_assert(std::is_same_v<SmemLayoutAtomD, void>, "Copy operation to shared memory is not supported");

using CopyThreadShape = Shape<_1, Int<SubgroupSize>>;

using Trait_C = Copy_Traits<GmemTiledCopyC, StrideC>;
using val_layout_load_C = decltype(make_layout(shape_div(typename Trait_C::BlockShape{}, CopyThreadShape{})));
using XE_Copy_C = decltype(make_tiled_copy(Copy_Atom<Trait_C, ElementC>{}, Layout<CopyThreadShape>{}, val_layout_load_C{}));

using Trait_D = Copy_Traits<GmemTiledCopyD, StrideD>;
using val_layout_store_D = decltype(make_layout(shape_div(typename Trait_D::BlockShape{}, CopyThreadShape{})));
using XE_Copy_D = decltype(make_tiled_copy(Copy_Atom<Trait_D, ElementD>{}, Layout<CopyThreadShape>{}, val_layout_store_D{}));

//remember this PR https://github.com/intel/sycl-tla/pull/565/files
private:
constexpr static bool is_source_supported = not cute::is_void_v<ElementC> && not cute::is_void_v<CopyOpG2R>;
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@jiyang1011 - The validation logic from PR #565 that sets is_source_supported to false when CopyOpG2R is void needs updating. With this PR's automatic ops selection, both CopyOpG2R and CopyOpR2G can now legitimately be void since make_block_2d_copy_* automatically selects appropriate operations.

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@jiyang1011 jiyang1011 Oct 23, 2025

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Could we set a default copy trait like XeCopyAuto or something else which will also call make_block_2d_copy_* ?

constexpr static bool is_destination_supported = not cute::is_void_v<ElementD> && not cute::is_void_v<CopyOpR2G>;
constexpr static bool is_source_supported = not cute::is_void_v<ElementC>;
constexpr static bool is_destination_supported = not cute::is_void_v<ElementD>;

constexpr static bool is_m_major_C = detail::is_m_major<StrideC>();
constexpr static bool is_m_major_D = detail::is_m_major<StrideD>();
Expand All @@ -154,6 +142,15 @@ class CollectiveEpilogue<
};
using TensorStorage = typename SharedStorage::TensorStorage;

// Helper to get tensor types
template<class Element, class Stride>
using TensorTypeC = decltype(make_tensor(make_gmem_ptr(static_cast<Element const*>(nullptr)),
make_layout(make_shape(int{}, int{}, int{}), Stride{})));

template<class Element, class Stride>
using TensorTypeD = decltype(make_tensor(make_gmem_ptr(static_cast<Element*>(nullptr)),
make_layout(make_shape(int{}, int{}, int{}), Stride{})));

// Host side epilogue arguments
struct Arguments {
typename FusionCallbacks::Arguments thread{};
Expand All @@ -166,8 +163,8 @@ class CollectiveEpilogue<
// Device side epilogue params
struct Params {
typename FusionCallbacks::Params thread{};
XE_Copy_C xe_load_c;
XE_Copy_D xe_store_d;
TensorTypeC<ElementC, StrideC> mC;
TensorTypeD<ElementD, StrideD> mD;
};

//
Expand All @@ -183,23 +180,13 @@ class CollectiveEpilogue<
// Optionally append 1s until problem shape is rank-4 in case its is only rank-3 (MNK)
auto problem_shape_MNKL = append<4>(problem_shape, 1);
auto [M, N, K, L] = problem_shape_MNKL;

XE_Copy_C xe_load_c = {};
if constexpr (is_source_supported) {
auto mC = make_tensor(make_gmem_ptr(args.ptr_C), make_layout(make_shape(M, N, L), args.dC));
xe_load_c = {xe_load_c.with(mC)};
}

XE_Copy_D xe_store_d = {};
if constexpr (is_destination_supported) {
auto mD = make_tensor(make_gmem_ptr(args.ptr_D), make_layout(make_shape(M, N, L), args.dD));
xe_store_d = {xe_store_d.with(mD)};
}
auto mC = make_tensor(make_gmem_ptr(args.ptr_C), make_layout(make_shape(M, N, L), args.dC));
auto mD = make_tensor(make_gmem_ptr(args.ptr_D), make_layout(make_shape(M, N, L), args.dD));

return {
FusionCallbacks::to_underlying_arguments(problem_shape, args.thread, workspace),
xe_load_c,
xe_store_d,
mC,
mD
};
}

Expand Down Expand Up @@ -270,6 +257,37 @@ class CollectiveEpilogue<
return fusion_callbacks.is_producer_load_needed();
}

template<typename Tensor>
CUTLASS_DEVICE auto reshape_with_unit_insertion(Tensor&& tensor) {
using namespace cute;

auto orig_layout = tensor.layout();
auto orig_shape = orig_layout.shape();
auto orig_stride = orig_layout.stride();

auto first_dim = get<0>(orig_shape);
auto outer_part = get<0>(first_dim);
auto inner_part = get<1>(first_dim);

auto first_stride = get<0>(orig_stride);
auto outer_stride = get<0>(first_stride);
auto inner_stride = get<1>(first_stride);

auto target_shape = make_shape(
make_shape(outer_part, _1{}),
get<0>(inner_part),
get<1>(inner_part)
);

auto target_stride = make_stride(
make_stride(outer_stride, _0{}),
get<0>(inner_stride),
get<1>(inner_stride)
);

return make_tensor(tensor.data(), make_layout(target_shape, target_stride));
Comment on lines +261 to +288

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Thanks for the revision!

IMHO, this seems to be a very good workaround to leverage new C, D copy atoms, if it'd work for any copy atoms used in epilogues.

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but then trC and trD has to modified for copy operation to be work properly

Sorry, do you mean further changes besides the ones currently in this PR?

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@anamikac-intel anamikac-intel Oct 24, 2025

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Legacy code seems to be restricted to XE_2D_U32x8x16_LD_N/ST_N operations (16×8 dimensions only). If 16×8 is the design target then no further changes needed otherwise, generalizing trC/trD requires decoupling from the fixed fragmentSize which appears tied to the accumulator layout (_8,_4,_4) suggesting 16×8 as the optimal dimension. Not sure fully waiting for peter to check

}

template<
class ProblemShapeMNKL,
class TileShapeMNK,
Expand All @@ -286,7 +304,6 @@ class CollectiveEpilogue<
TiledMma tiled_mma,
int thread_idx) {

(void) tiled_mma;
using namespace cute;

static_assert(cute::rank(CtaTileMNK{}) == 3, "CtaTileMNK must be rank-3: [CTA_M, CTA_N, CTA_K]");
Expand All @@ -297,12 +314,11 @@ class CollectiveEpilogue<
static constexpr auto BLK_M = get<0>(CtaTileMNK{});
static constexpr auto BLK_N = get<1>(CtaTileMNK{});
static constexpr auto BLK_K = get<2>(CtaTileMNK{});
// static_assert(is_same_v<typename TiledMma::ThrLayoutVMNK, int>, "assertation fail");
static constexpr auto ATOM_M = get<1>(typename TiledMma::ThrLayoutVMNK{}.shape());
static constexpr auto ATOM_N = get<2>(typename TiledMma::ThrLayoutVMNK{}.shape());
static constexpr auto ATOM_K = get<3>(typename TiledMma::ThrLayoutVMNK{}.shape());
static_assert(

static_assert(
BLK_M % ATOM_M == 0 &&
BLK_N % ATOM_N == 0 &&
BLK_K % ATOM_K == 0,
Expand All @@ -316,46 +332,46 @@ class CollectiveEpilogue<
static constexpr int FragsN = get<1>(SubgroupTileShape{}) / get<1>(MmaAtomShape()); // B frags per sub_group

static constexpr int FragmentSize = (get<0>(MmaAtomShape()) * get<1>(MmaAtomShape())) / SubgroupSize;

// Indexing variables
auto [M, N, K, L] = problem_shape_mnkl;
auto [m_coord, n_coord, k_coord, l_coord] = tile_coord_mnkl;
auto m_sg = get_sub_group_id() / ATOM_N;
auto n_sg = get_sub_group_id() % ATOM_N;

auto mn_shape = shape(typename decltype(params.xe_store_d)::Tiler_MN{});

auto sg_local_m_coord = get_sub_group_id() / ATOM_N;
auto sg_local_n_coord = get_sub_group_id() % ATOM_N;

auto sg_m_coord = m_coord * ATOM_M + sg_local_m_coord;
auto sg_n_coord = n_coord * ATOM_N + sg_local_n_coord;
auto sg_coord = make_coord(sg_m_coord, sg_n_coord, k_coord, l_coord);


auto wg_coord = make_coord(m_coord, n_coord, k_coord, l_coord);
bool is_C_load_needed = is_source_supported && fusion_callbacks.is_C_load_needed();

auto batch_idx = get<3>(wg_coord);
auto copy_c = get_block_2d_copy_C<CopyOpG2R>(tiled_mma, params.mC(_,_,batch_idx));
auto copy_d = get_block_2d_copy_D<CopyOpR2G>(tiled_mma, params.mD(_,_,batch_idx));



// Represent the full output tensor
Tensor mD_mnl = cute::get_xe_tensor(make_shape(M,N,L));

// Tile the output tensor per WG and select the tile for current WG
Tensor g_wg_D = local_tile(mD_mnl, take<0,2>(CtaTileMNK{}), make_coord(m_coord,n_coord,l_coord)); // (BLK_M,BLK_N)

// Tile the output tensor per SG and select tile for the current SG
Tensor gD = local_tile(g_wg_D, take<0,2>(SubgroupTileShape{}), make_coord(m_sg,n_sg)); // (SG_M,SG_N)
// Tile the output tensor for the current workgroup
Tensor gD = local_tile(mD_mnl, take<0,2>(CtaTileMNK{}), remove<2>(wg_coord)); // (BLK_M,BLK_N)

auto thread_xe_load_c = params.xe_load_c.get_thread_slice(thread_idx);
Tensor tCgC = thread_xe_load_c.partition_S(gD);
// Get thread-level partitioning across the entire workgroup tile
auto thread_xe_load_c = copy_c.get_thread_slice(thread_idx);
Tensor tCgC = reshape_with_unit_insertion(thread_xe_load_c.partition_S(gD));

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What's the purpose of this reshape and why is it needed?


auto thread_xe_store_d = params.xe_store_d.get_thread_slice(thread_idx);
Tensor tCgD = thread_xe_store_d.partition_D(gD);
auto thread_xe_store_d = copy_d.get_thread_slice(thread_idx);
Tensor tCgD = reshape_with_unit_insertion(thread_xe_store_d.partition_D(gD));

Tensor trC = make_tensor<typename TiledMma::ValTypeC>(Shape<Int<FragmentSize>>{});
Tensor trD_compute = make_tensor<ElementCompute>(Shape<Int<FragmentSize>>{});

// Because Sm90 uses shared memory, they are not tied to using the same accumulator values
// for MMA and Epilogue. But because we are operating directly in the accumulators, we need to be
// sure that we are operating on the same values.
ThrCopy thread_g2r = params.xe_load_c.get_slice(thread_idx);
ThrCopy thread_g2r = copy_c.get_slice(thread_idx);
auto mn_shape = shape(typename decltype(copy_d)::Tiler_MN{});

// OOB predication for tile quantization "residue"
// Absolute coordinate tensors (dynamic)
Expand All @@ -364,7 +380,7 @@ class CollectiveEpilogue<
Tensor cD_mn = local_tile(mD_crd, take<0,2>(CtaTileMNK{}), make_coord(m_coord, n_coord)); // (CTA_M,CTA_N)
Tensor tRS_cD_mn = thread_g2r.partition_S(flat_divide(cD_mn, mn_shape)); // (G2R,G2R_M,G2R_N,EPI_M,EPI_N)

Tensor tRS_cD = make_coord_tensor(tRS_cD_mn.layout()); // (G2R,G2R_M,G2R_N,EPI_M,EPI_N)
Tensor tRS_cD = make_coord_tensor(tRS_cD_mn.layout());

// Get the fusion callbacks
// Arguments passed here relate to sub-group tiles, rather than CTA (work-group) tiles
Expand All @@ -376,7 +392,7 @@ class CollectiveEpilogue<
sg_coord,
tiled_mma,
mn_shape,
params.xe_store_d,
copy_d,
cD,
residue_mn,
tRS_cD,
Expand All @@ -398,7 +414,8 @@ class CollectiveEpilogue<
FragsM * FragsN * FragmentSize * SubgroupSize * ATOM_M * ATOM_N * ATOM_K;
constexpr int MN = get<0>(CtaTileMNK{}) * get<1>(CtaTileMNK{});
static_assert(ValuesLoaded == MN, "the total elements loaded by all threads should be the same as MxN" );



auto synchronize = [&] () {};
CUTLASS_PRAGMA_UNROLL
for (int epi_n = 0; epi_n < FragsN; epi_n++) {
Expand All @@ -407,7 +424,7 @@ class CollectiveEpilogue<
cst_callbacks.begin_loop(epi_m, epi_n);

if (is_C_load_needed) {
copy(params.xe_load_c, tCgC(_, epi_m, epi_n), trC);
copy(copy_c, tCgC(_, epi_m, epi_n), trC);
}

cst_callbacks.previsit(epi_m, epi_n, 0, is_C_load_needed);
Expand All @@ -419,21 +436,23 @@ class CollectiveEpilogue<
trD_compute_frag(epi_v) = cst_callbacks.visit(acc_frag_mn(epi_v), epi_v, epi_m, epi_n);
}
cst_callbacks.reduce(nullptr, synchronize, epi_m, epi_n, (epi_m == FragsM - 1 && epi_n == FragsN - 1), trD_compute_frag);

if constexpr (is_destination_supported) {
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < size(trD_compute_frag); ++i) {
trD_frag(i) = cutlass::NumericArrayConverter<ElementOutput, ElementCompute, FragmentSize>{}(trD_compute_frag(i));
}
copy(params.xe_store_d, trD, tCgD(_, epi_m, epi_n));
copy(copy_d, trD, tCgD(_, epi_m, epi_n));
}

cst_callbacks.end_loop(epi_m, epi_n);

}
}

cst_callbacks.end();
}

}

private:
Params const& params;
Expand All @@ -447,4 +466,4 @@ class CollectiveEpilogue<
} // namespace epilogue
} // namespace cutlass

/////////////////////////////////////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////////////////////////////////
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