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/*! \file
    \brief Template for a double-buffered threadblock-scoped GEMM kernel.
*/

#pragma once

#include "cutlass/aligned_buffer.h"
#include "cutlass/arch/memory.h"
#include "cutlass/array.h"
#include "cutlass/cutlass.h"
#include "cutlass/gemm/gemm.h"
#include "cutlass/matrix_shape.h"
#include "cutlass/numeric_types.h"

#include "cutlass_extensions/gemm/threadblock/dq_mma_base.h"
#include "cutlass_extensions/gemm/warp/mma_tensorop_dequantizer.h"
#include "cutlass_extensions/interleaved_numeric_conversion.h"

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

namespace cutlass
{
namespace gemm
{
namespace threadblock
{

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

/// Structure to compute the matrix product targeting CUDA cores and SIMT math
/// instructions.
template <
    /// Size of the Gemm problem - concept: gemm::GemmShape<>
    typename Shape_,
    /// Iterates over tiles of A operand in global memory
    //  (concept: ReadableTileIterator | ForwardTileIterator |
    //  MaskedTileIterator)
    typename IteratorA_,
    /// Iterates over tiles of A operand in shared memory
    /// (concept: WriteableTileIterator | RandomAccessTileIterator)
    typename SmemIteratorA_,
    /// Cache operation for operand A
    cutlass::arch::CacheOperation::Kind CacheOpA,
    /// Iterates over tiles of B operand in global memory
    //  (concept: ReadableTileIterator | ForwardTileIterator |
    //  MaskedTileIterator)
    typename IteratorB_,
    /// Iterates over tiles of B operand in shared memory
    /// (concept: WriteableTileIterator | RandomAccessTileIterator)
    typename SmemIteratorB_,
    /// Cache operation for operand B
    cutlass::arch::CacheOperation::Kind CacheOpB,
    /// Data type for the scales
    typename IteratorScale_,
    /// Iterators over scales in shared memory
    typename SmemIteratorScale_,
    /// Data type of accumulator matrix
    typename ElementC_,
    /// Data type of accumulator matrix
    typename LayoutC_,
    /// Policy describing tuning details (concept: MmaPolicy)
    typename Policy_,
    /// Number of stages,
    int Stages,
    /// Converter for B matrix applited immediately after the LDS
    typename TransformBAfterLDS_,
    /// The quantization operator being used
    WeightOnlyQuantOp QuantOp_,
    /// Use zfill or predicate for out-of-bound cp.async
    SharedMemoryClearOption SharedMemoryClear>
class DqMmaMultistage<Shape_, IteratorA_, SmemIteratorA_, CacheOpA, IteratorB_, SmemIteratorB_, CacheOpB,
    IteratorScale_, SmemIteratorScale_, ElementC_, LayoutC_, Policy_, Stages, TransformBAfterLDS_, QuantOp_,
    SharedMemoryClear, std::enable_if_t<isFinegrained(QuantOp_)>>
    : public DqMmaBase<Shape_, Policy_, typename IteratorScale_::Element, Stages, QuantOp_>
{
public:
    ///< Base class
    using Base = DqMmaBase<Shape_, Policy_, typename IteratorScale_::Element, Stages, QuantOp_>;
    ///< Size of the Gemm problem - concept: gemm::GemmShape<>
    using Shape = Shape_;
    ///< Iterates over tiles of A operand in global memory
    using IteratorA = IteratorA_;
    ///< Iterates over tiles of B operand in global memory
    using IteratorB = IteratorB_;
    ///< Data type of accumulator matrix
    using ElementC = ElementC_;
    ///< Layout of accumulator matrix
    using LayoutC = LayoutC_;
    ///< Policy describing tuning details
    using Policy = Policy_;

    using IteratorScale = IteratorScale_;
    using ElementScale = typename IteratorScale::Element;
    using LayoutScale = typename IteratorScale::Layout;

    using SmemIteratorA = SmemIteratorA_;
    using SmemIteratorB = SmemIteratorB_;
    using SmemIteratorScale = SmemIteratorScale_;

    static cutlass::arch::CacheOperation::Kind const kCacheOpA = CacheOpA;
    static cutlass::arch::CacheOperation::Kind const kCacheOpB = CacheOpB;

    using TransformBAfterLDS = TransformBAfterLDS_;

    static constexpr WeightOnlyQuantOp QuantOp = QuantOp_;
    //
    // Dependent types
    //

    /// Fragment of accumulator tile
    using FragmentC = typename Policy::Operator::FragmentC;

    /// Warp-level Mma
    using Operator = typename Policy::Operator;

    /// Minimum architecture is Sm80 to support cp.async
    using ArchTag = arch::Sm80;

    using Dequantizer = warp::MmaTensorOpDequantizer<Operator, typename Base::WarpGemm, Operand::kB, ElementScale,
        LayoutScale, 32, QuantOp>;

    /// Complex transform on A operand
    static ComplexTransform const kTransformA = Operator::kTransformA;

    /// Complex transform on B operand
    static ComplexTransform const kTransformB = Operator::kTransformB;

    static_assert(Base::SharedStorage::ShapeScale::kRow == Stages, "");
    static_assert(Base::SharedStorage::ShapeScale::kColumn == Shape::kN, "");

    /// Internal structure exposed for introspection.
    struct Detail
    {

        static_assert(Base::kWarpGemmIterations > 1,
            "The pipelined structure requires at least two warp-level "
            "GEMM operations.");

        /// Number of cp.async instructions to load one stage of operand A
        static int const AsyncCopyIterationsPerStageA = IteratorA::ThreadMap::Iterations::kCount;

        /// Number of cp.async instructions to load one stage of operand B
        static int const AsyncCopyIterationsPerStageB = IteratorB::ThreadMap::Iterations::kCount;

        /// Number of stages
        static int const kStages = Stages;

        /// Number of cp.async instructions to load on group of operand A
        static int const kAccessesPerGroupA
            = (AsyncCopyIterationsPerStageA + Base::kWarpGemmIterations - 1) / Base::kWarpGemmIterations;

        /// Number of cp.async instructions to load on group of operand B
        static int const kAccessesPerGroupB
            = (AsyncCopyIterationsPerStageB + Base::kWarpGemmIterations - 1) / Base::kWarpGemmIterations;
    };

private:
    using WarpFragmentA = typename Operator::FragmentA;
    using WarpFragmentB = typename Operator::FragmentB;
    Dequantizer warp_dequantizer_;

    using ElementB = typename IteratorB::Element;
    using LayoutDetailsForB = kernel::LayoutDetailsB<ElementB, ArchTag>;

    static constexpr bool RequiresTileInterleave
        = layout::IsColumnMajorTileInterleave<typename LayoutDetailsForB::Layout>::value;
    static_assert(!RequiresTileInterleave || (RequiresTileInterleave && (Shape::kK == LayoutDetailsForB::ThreadblockK)),
        "Layout K must match threadblockK");

private:
    //
    // Data members
    //

    /// Iterator to write threadblock-scoped tile of A operand to shared memory
    SmemIteratorA smem_iterator_A_;

    /// Iterator to write threadblock-scoped tile of B operand to shared memory
    SmemIteratorB smem_iterator_B_;

    /// Iterator to write threadblock-scoped tile of scale and zero operand to shared memory
    SmemIteratorScale smem_iterator_scale_;

public:
    /// Construct from tensor references
    CUTLASS_DEVICE
    DqMmaMultistage(
        ///< Shared storage needed for internal use by threadblock-scoped GEMM
        typename Base::SharedStorage& shared_storage,
        /// The group size for quantization
        int group_size,
        ///< ID within the threadblock
        int thread_idx,
        ///< ID of warp
        int warp_idx,
        ///< ID of each thread within a warp
        int lane_idx)
        : Base(shared_storage, thread_idx, warp_idx, lane_idx)
        , warp_dequantizer_({shared_storage.operand_scale.data(), LayoutScale(Shape::kN)},
              {shared_storage.operand_zero.data(), LayoutScale(Shape::kN)},
              (warp_idx % (Base::WarpCount::kM * Base::WarpCount::kN)) / Base::WarpCount::kM, lane_idx)
        , smem_iterator_A_(shared_storage.operand_A_ref(), thread_idx)
        , smem_iterator_B_(shared_storage.operand_B_ref(), thread_idx)
        , smem_iterator_scale_(LayoutScale(Shape::kN), shared_storage.operand_scale.data(),
              shared_storage.operand_zero.data(), {Base::kStages, Shape::kN}, thread_idx, group_size)
    {
        // Compute warp location within threadblock tile by mapping the warp_id to
        // three coordinates:
        //   _m: the warp's position within the threadblock along the M dimension
        //   _n: the warp's position within the threadblock along the N dimension
        //   _k: the warp's position within the threadblock along the K dimension

        int warp_idx_mn = warp_idx % (Base::WarpCount::kM * Base::WarpCount::kN);
        int warp_idx_k = warp_idx / (Base::WarpCount::kM * Base::WarpCount::kN);

        int warp_idx_m = warp_idx_mn % Base::WarpCount::kM;
        int warp_idx_n = warp_idx_mn / Base::WarpCount::kM;

        // Add per-warp offsets in units of warp-level tiles
        this->warp_tile_iterator_A_.add_tile_offset({warp_idx_m, Base::kWarpGemmIterations * warp_idx_k});
        this->warp_tile_iterator_B_.add_tile_offset({Base::kWarpGemmIterationsForB * warp_idx_k, warp_idx_n});
    }

    CUTLASS_DEVICE
    void copy_scales_and_advance(IteratorScale& iterator_scale, int stage = -1, int k_iter = -1)
    {
        static_assert(IteratorScale::Shape::kRow == 1, "Scale stride must be 1.");

        typename IteratorScale::AccessType* gmem_scale_ptr = iterator_scale.get_scale();
        typename IteratorScale::AccessType* gmem_zero_ptr = iterator_scale.get_zero();

        typename IteratorScale::AccessType* smem_scale_ptr
            = reinterpret_cast<typename IteratorScale::AccessType*>(this->smem_iterator_scale_.get_scale());
        typename IteratorScale::AccessType* smem_zero_ptr
            = reinterpret_cast<typename IteratorScale::AccessType*>(this->smem_iterator_scale_.get_zero());

        int const kSrcBytes = sizeof_bits<typename IteratorScale::Element>::value * IteratorScale::kAlignment / 8;

        cutlass::arch::cp_async<kSrcBytes, kCacheOpB>(smem_scale_ptr, gmem_scale_ptr, iterator_scale.valid());

        if (gmem_zero_ptr != nullptr)
        {
            cutlass::arch::cp_async<kSrcBytes, kCacheOpB>(smem_zero_ptr, gmem_zero_ptr, iterator_scale.valid());
        }

        if (iterator_scale.group_size_ == 64)
        {
            iterator_scale.add_tile_offset({1, 0});
        }
        else if (iterator_scale.group_size_ == 128)
        {
            if (iterator_scale.row_groupsize64_ & 0x1)
            {
                iterator_scale.add_tile_offset({1, 0});
            }
        }

        iterator_scale.row_groupsize64_++;

        this->smem_iterator_scale_.add_tile_offset({1, 0});
    }

    CUTLASS_DEVICE
    void copy_tiles_and_advance(IteratorA& iterator_A, IteratorB& iterator_B, IteratorScale& iterator_scale,
        int group_start_A = 0, int group_start_B = 0)
    {
        iterator_A.set_iteration_index(group_start_A * IteratorA::kAccessesPerVector);
        this->smem_iterator_A_.set_iteration_index(group_start_A);

        // Async Copy for operand A
        CUTLASS_PRAGMA_UNROLL
        for (int j = 0; j < Detail::kAccessesPerGroupA; ++j)
        {
            if (group_start_A + j < Detail::AsyncCopyIterationsPerStageA)
            {
                typename IteratorA::AccessType* dst_ptr
                    = reinterpret_cast<typename IteratorA::AccessType*>(this->smem_iterator_A_.get());

                int const kSrcBytes = sizeof_bits<typename IteratorA::Element>::value
                    * IteratorA::ThreadMap::kElementsPerAccess / IteratorA::kAccessesPerVector / 8;

                CUTLASS_PRAGMA_UNROLL
                for (int v = 0; v < IteratorA::kAccessesPerVector; ++v)
                {
                    auto gmem_ptr = iterator_A.get();

                    if (SharedMemoryClear == SharedMemoryClearOption::kZfill)
                    {
                        cutlass::arch::cp_async_zfill<kSrcBytes, kCacheOpA>(dst_ptr + v, gmem_ptr, iterator_A.valid());
                    }
                    else
                    {
                        cutlass::arch::cp_async<kSrcBytes, kCacheOpA>(dst_ptr + v, gmem_ptr, iterator_A.valid());
                    }

                    ++iterator_A;
                }

                ++this->smem_iterator_A_;
            }
        }

        iterator_B.set_iteration_index(group_start_B * IteratorB::kAccessesPerVector);
        this->smem_iterator_B_.set_iteration_index(group_start_B);

        // Async Copy for operand B
        CUTLASS_PRAGMA_UNROLL
        for (int j = 0; j < Detail::kAccessesPerGroupB; ++j)
        {
            if (group_start_B + j < Detail::AsyncCopyIterationsPerStageB)
            {
                typename IteratorB::AccessType* dst_ptr
                    = reinterpret_cast<typename IteratorB::AccessType*>(this->smem_iterator_B_.get());

                int const kSrcBytes = sizeof_bits<typename IteratorB::Element>::value
                    * IteratorB::ThreadMap::kElementsPerAccess / IteratorB::kAccessesPerVector / 8;

                CUTLASS_PRAGMA_UNROLL
                for (int v = 0; v < IteratorB::kAccessesPerVector; ++v)
                {
                    auto gmem_ptr = iterator_B.get();

                    if (SharedMemoryClear == SharedMemoryClearOption::kZfill)
                    {
                        cutlass::arch::cp_async_zfill<kSrcBytes, kCacheOpB>(dst_ptr + v, gmem_ptr, iterator_B.valid());
                    }
                    else
                    {
                        cutlass::arch::cp_async<kSrcBytes, kCacheOpB>(dst_ptr + v, gmem_ptr, iterator_B.valid());
                    }

                    ++iterator_B;
                }
                ++this->smem_iterator_B_;
            }
        }
    }

    /// Perform a threadblock-scoped matrix multiply-accumulate
    CUTLASS_DEVICE
    void operator()(
        ///< problem size of GEMM
        int gemm_k_iterations,
        ///< destination accumulator tile
        FragmentC& accum,
        ///< iterator over A operand in global memory
        IteratorA iterator_A,
        ///< iterator over B operand in global memory
        IteratorB iterator_B,
        ///< iterator over scale operand in global memory
        IteratorScale iterator_scale,
        ///< initial value of accumulator
        FragmentC const& src_accum)
    {

        //
        // Prologue
        //

        TransformBAfterLDS lds_converter;

        // Issue several complete stages
        CUTLASS_PRAGMA_UNROLL
        for (int stage = 0; stage < Base::kStages - 1; ++stage, --gemm_k_iterations)
        {

            iterator_A.clear_mask(gemm_k_iterations == 0);
            iterator_B.clear_mask(gemm_k_iterations == 0);
            iterator_scale.clear_mask(gemm_k_iterations == 0);

            iterator_A.set_iteration_index(0);
            this->smem_iterator_A_.set_iteration_index(0);

            // Async Copy for operand A
            CUTLASS_PRAGMA_UNROLL
            for (int j = 0; j < Detail::AsyncCopyIterationsPerStageA; ++j)
            {
                typename IteratorA::AccessType* dst_ptr
                    = reinterpret_cast<typename IteratorA::AccessType*>(this->smem_iterator_A_.get());

                CUTLASS_PRAGMA_UNROLL
                for (int v = 0; v < IteratorA::kAccessesPerVector; ++v)
                {
                    int const kSrcBytes = sizeof_bits<typename IteratorA::Element>::value
                        * IteratorA::ThreadMap::kElementsPerAccess / IteratorA::kAccessesPerVector / 8;

                    int src_bytes = (iterator_A.valid() ? kSrcBytes : 0);

                    cutlass::arch::cp_async_zfill<kSrcBytes, kCacheOpA>(
                        dst_ptr + v, iterator_A.get(), iterator_A.valid());

                    ++iterator_A;
                }

                ++this->smem_iterator_A_;
            }

            iterator_B.set_iteration_index(0);
            this->smem_iterator_B_.set_iteration_index(0);

            // Async Copy for operand B
            CUTLASS_PRAGMA_UNROLL
            for (int j = 0; j < Detail::AsyncCopyIterationsPerStageB; ++j)
            {
                typename IteratorB::AccessType* dst_ptr
                    = reinterpret_cast<typename IteratorB::AccessType*>(this->smem_iterator_B_.get());

                CUTLASS_PRAGMA_UNROLL
                for (int v = 0; v < IteratorB::kAccessesPerVector; ++v)
                {
                    int const kSrcBytes = sizeof_bits<typename IteratorB::Element>::value
                        * IteratorB::ThreadMap::kElementsPerAccess / IteratorB::kAccessesPerVector / 8;

                    cutlass::arch::cp_async_zfill<kSrcBytes, kCacheOpB>(
                        dst_ptr + v, iterator_B.get(), iterator_B.valid());

                    ++iterator_B;
                }

                ++this->smem_iterator_B_;
            }

            copy_scales_and_advance(iterator_scale, stage, gemm_k_iterations);

            // Move to the next stage
            iterator_A.add_tile_offset({0, 1});
            iterator_B.add_tile_offset({1, 0});

            this->smem_iterator_A_.add_tile_offset({0, 1});
            this->smem_iterator_B_.add_tile_offset({1, 0});

            // Defines the boundary of a stage of cp.async.
            cutlass::arch::cp_async_fence();
        }

        // Perform accumulation in the 'd' output operand
        accum = src_accum;

        //
        // Clear the remaining tiles of SMEM. This is a functional requirement for some kernels
        // so that all accumulator elements outside the GEMM footprint are zero.
        //

        if (SharedMemoryClear == SharedMemoryClearOption::kClearLastStage)
        {

            /// Iterator to write threadblock-scoped tile of A operand to shared memory
            SmemIteratorA last_smem_iterator_A(this->smem_iterator_A_);

            typename IteratorA::AccessType zero_A;
            zero_A.clear();

            last_smem_iterator_A.set_iteration_index(0);

            // Async Copy for operand A
            CUTLASS_PRAGMA_UNROLL
            for (int j = 0; j < Detail::AsyncCopyIterationsPerStageA; ++j)
            {

                typename IteratorA::AccessType* dst_ptr
                    = reinterpret_cast<typename IteratorA::AccessType*>(last_smem_iterator_A.get());

                *dst_ptr = zero_A;

                ++last_smem_iterator_A;
            }

            /// Iterator to write threadblock-scoped tile of B operand to shared memory
            SmemIteratorB last_smem_iterator_B(this->smem_iterator_B_);
            typename IteratorB::AccessType zero_B;

            zero_B.clear();
            last_smem_iterator_B.set_iteration_index(0);

            // Async Copy for operand B
            CUTLASS_PRAGMA_UNROLL
            for (int j = 0; j < Detail::AsyncCopyIterationsPerStageB; ++j)
            {

                typename IteratorB::AccessType* dst_ptr
                    = reinterpret_cast<typename IteratorB::AccessType*>(last_smem_iterator_B.get());

                *dst_ptr = zero_B;

                ++last_smem_iterator_B;
            }
        }

        // Wait until we have at least one committed global fetch stage. (#uncommitted = Base::kStages - 1 - #committed)
        cutlass::arch::cp_async_wait<Base::kStages - 2>();
        __syncthreads();

        // Pair of fragments used to overlap shared memory loads and math
        // instructions
        WarpFragmentA warp_frag_A[2];
        WarpFragmentB warp_frag_B[2];
        typename Dequantizer::FragmentScale warp_frag_scales;
        typename Dequantizer::FragmentZero warp_frag_zeros;

        Operator warp_mma;

        this->warp_tile_iterator_A_.set_kgroup_index(0);
        this->warp_tile_iterator_B_.set_kgroup_index(0);

        this->warp_tile_iterator_A_.load(warp_frag_A[0]);
        this->warp_tile_iterator_B_.load(warp_frag_B[0]);

        warp_dequantizer_.load(warp_frag_scales, warp_frag_zeros);

        ++this->warp_tile_iterator_A_;
        ++this->warp_tile_iterator_B_;
        warp_dequantizer_.add_pointer_offset(Shape::kN);

        iterator_A.clear_mask(gemm_k_iterations == 0);
        iterator_B.clear_mask(gemm_k_iterations == 0);
        iterator_scale.clear_mask(gemm_k_iterations == 0);

        int smem_write_stage_idx = Base::kStages - 1;
        int smem_read_stage_idx = 0;

        //
        // Mainloop
        //

        CUTLASS_GEMM_LOOP
        for (; gemm_k_iterations > (-Base::kStages + 1);)
        {
            //
            // Loop over GEMM K dimension
            //

            // Computes a warp-level GEMM on data held in shared memory
            // Each "warp_mma_k" refers to a warp-level matrix multiply-accumulate
            CUTLASS_PRAGMA_UNROLL
            for (int warp_mma_k = 0; warp_mma_k < Base::kWarpGemmIterations; ++warp_mma_k)
            {

                // Load warp-level tiles from shared memory, wrapping to k offset if
                // this is the last group as the case may be.

                this->warp_tile_iterator_A_.set_kgroup_index((warp_mma_k + 1) % Base::kWarpGemmIterations);
                this->warp_tile_iterator_A_.load(warp_frag_A[(warp_mma_k + 1) % 2]);
                ++this->warp_tile_iterator_A_;

                const int warp_tileB_k_compute_offset = warp_mma_k % Base::kNumKIterationsPerWarpBLoad;
                const int warp_tileB_k_load_offset = warp_mma_k / Base::kNumKIterationsPerWarpBLoad;
                if (warp_tileB_k_compute_offset == Base::kNumKIterationsPerWarpBLoad - 1)
                {
                    this->warp_tile_iterator_B_.set_kgroup_index(
                        (warp_tileB_k_load_offset + 1) % Base::kWarpGemmIterationsForB);
                    this->warp_tile_iterator_B_.load(warp_frag_B[(warp_tileB_k_load_offset + 1) % 2]);
                    ++this->warp_tile_iterator_B_;
                }

                typename TransformBAfterLDS::result_type converted_frag_B
                    = lds_converter(warp_frag_B[warp_tileB_k_load_offset % 2]);
                warp_dequantizer_.dequantize(converted_frag_B, warp_frag_scales, warp_frag_zeros);

                run_warp_mma(
                    warp_mma, accum, warp_frag_A[warp_mma_k % 2], converted_frag_B, accum, warp_tileB_k_compute_offset);

                // Issue global->shared copies for the this stage
                if (warp_mma_k < Base::kWarpGemmIterations - 1)
                {
                    int group_start_iteration_A, group_start_iteration_B;

                    group_start_iteration_A = warp_mma_k * Detail::kAccessesPerGroupA;
                    group_start_iteration_B = warp_mma_k * Detail::kAccessesPerGroupB;

                    copy_tiles_and_advance(
                        iterator_A, iterator_B, iterator_scale, group_start_iteration_A, group_start_iteration_B);

                    // This is the first group of a given stage, so we issue the loads for the B scales immediately.
                    if (group_start_iteration_B == 0)
                    {
                        copy_scales_and_advance(iterator_scale);
                    }
                }

                if (warp_mma_k + 2 == Base::kWarpGemmIterations)
                {
                    int group_start_iteration_A, group_start_iteration_B;
                    group_start_iteration_A = (warp_mma_k + 1) * Detail::kAccessesPerGroupA;
                    group_start_iteration_B = (warp_mma_k + 1) * Detail::kAccessesPerGroupB;

                    copy_tiles_and_advance(
                        iterator_A, iterator_B, iterator_scale, group_start_iteration_A, group_start_iteration_B);

                    // Inserts a memory fence between stages of cp.async instructions.
                    cutlass::arch::cp_async_fence();

                    // Wait until we have at least one committed global fetch stage. (#uncommitted = Base::kStages - 1 -
                    // #committed)
                    arch::cp_async_wait<Base::kStages - 2>();
                    __syncthreads();

                    // Move to the next stage
                    iterator_A.add_tile_offset({0, 1});
                    iterator_B.add_tile_offset({1, 0});

                    this->smem_iterator_A_.add_tile_offset({0, 1});
                    this->smem_iterator_B_.add_tile_offset({1, 0});

                    // Add negative offsets to return iterators to the 'start' of the
                    // circular buffer in shared memory
                    if (smem_write_stage_idx == (Base::kStages - 1))
                    {
                        this->smem_iterator_A_.add_tile_offset({0, -Base::kStages});
                        this->smem_iterator_B_.add_tile_offset({-Base::kStages, 0});
                        this->smem_iterator_scale_.add_tile_offset({-Base::kStages, 0});
                        smem_write_stage_idx = 0;
                    }
                    else
                    {
                        ++smem_write_stage_idx;
                    }

                    if (smem_read_stage_idx == (Base::kStages - 1))
                    {
                        this->warp_tile_iterator_A_.add_tile_offset(
                            {0, -Base::kStages * Policy::kPartitionsK * Base::kWarpGemmIterations});
                        this->warp_tile_iterator_B_.add_tile_offset(
                            {-Base::kStages * Policy::kPartitionsK * Base::kWarpGemmIterationsForB, 0});
                        warp_dequantizer_.add_pointer_offset(-Base::kStages * Shape::kN);
                        smem_read_stage_idx = 0;
                    }
                    else
                    {
                        ++smem_read_stage_idx;
                    }

                    --gemm_k_iterations;
                    iterator_A.clear_mask(gemm_k_iterations == 0);
                    iterator_B.clear_mask(gemm_k_iterations == 0);
                    iterator_scale.clear_mask(gemm_k_iterations == 0);
                }
            }

            // Load the scale needed for the next tile iteration.
            warp_dequantizer_.load(warp_frag_scales, warp_frag_zeros);
            // Update internal pointer to set of scales in shared memory.
            warp_dequantizer_.add_pointer_offset(Shape::kN);
        }

        if (SharedMemoryClear == SharedMemoryClearOption::kZfill)
        {
            // commit and drain all pending and predicated LDGSTS pnz from the GEMM mainloop
            cutlass::arch::cp_async_fence();
            cutlass::arch::cp_async_wait<0>();
            __syncthreads();
        }
    }
};

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

} // namespace threadblock
} // namespace gemm
} // namespace cutlass

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