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/*! \file
  \brief Epilogue for threadblock scoped GEMMs using Tensor Ops.

  The epilogue rearranges the result of a matrix product through shared memory
  to match canonical tensor layouts in global memory. Epilogues support
  conversion and reduction operations.

*/

#pragma once

#include "cutlass/cutlass.h"
#include "cutlass/numeric_types.h"
#include "cutlass/array.h"
#include "cutlass/layout/matrix.h"
#include "cutlass/layout/tensor.h"
#include "cutlass/matrix_shape.h"
#include "cutlass/tensor_ref.h"
#include "cutlass/transform/pitch_linear_thread_map.h"
#include "cutlass/epilogue/threadblock/output_tile_thread_map.h"
#include "cutlass/arch/arch.h"
#include "cutlass/arch/memory.h"
#include "cutlass/epilogue/threadblock/predicated_tile_iterator_params.h"

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

namespace cutlass {

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

namespace epilogue {
namespace threadblock {

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

/// Tile iterator used to load and store output tile from shared memory in
/// epilogue.
///
/// Satisfies: ReadableTileIterator | PredicatedTileIterator |
/// ForwardTileIterator
///
template <typename ThreadMap_,  ///< Thread map (conept: OutputTileThreadMap)
          typename Element_     ///< Element data type
          >
class PredicatedTileIterator {
public:
    using ThreadMap = ThreadMap_;
    using Shape = typename ThreadMap::Shape;

    using Element = Element_;

    using Layout = layout::RowMajor;
    using TensorRef = TensorRef<Element, Layout>;
    using ConstTensorRef = typename TensorRef::ConstTensorRef;

    using Index = typename Layout::Index;
    using LongIndex = typename Layout::LongIndex;
    using TensorCoord = MatrixCoord;

    static int const kElementsPerAccess = ThreadMap::kElementsPerAccess;
    static int const kThreads = ThreadMap::kThreads;
    static int const kIterations = ThreadMap::Count::kTile;

    static_assert(ThreadMap::Iterations::kRow > 0,
                  "ThreadMap::Iterations::kRow must be > 0");
    static_assert(ThreadMap::Iterations::kGroup > 0,
                  "ThreadMap::Iterations::kGroup must be > 0");
    static_assert(ThreadMap::Iterations::kCluster > 0,
                  "ThreadMap::Iterations::kCluster must be > 0");
    static_assert(ThreadMap::Iterations::kColumn > 0,
                  "ThreadMap::Iterations::kColumn must be > 0");

    /// Fragment object
    using Fragment = Array<Element, ThreadMap::Iterations::kColumn *
                                            ThreadMap::Iterations::kRow *
                                            ThreadMap::Iterations::kGroup *
                                            ThreadMap::Iterations::kCluster *
                                            ThreadMap::kElementsPerAccess>;

    /// Memory access size
    using AccessType = AlignedArray<Element, ThreadMap::kElementsPerAccess>;

    //
    // Parameters struct
    //

    /// Uses a non-template class
    struct Params : PredicatedTileIteratorParams {
        CUTLASS_HOST_DEVICE
        Params() {}

        CUTLASS_HOST_DEVICE
        Params(Layout const& layout)
                : PredicatedTileIteratorParams(
                          layout.stride(0) * int(sizeof(AccessType)) /
                                  kElementsPerAccess,
                          make_OutputTileThreadMapDesc<ThreadMap>()) {}
    };

    /// Mask object
    struct Mask {
        static int const kCount = ThreadMap::Iterations::kColumn;

        /// Predicate state
        bool predicates[kCount];

        //
        // Mask
        //
        CUTLASS_HOST_DEVICE
        Mask() { enable(); }

        ///< Efficiently disables all accesses guarded by mask
        CUTLASS_HOST_DEVICE void clear() {
            CUTLASS_PRAGMA_UNROLL
            for (int i = 0; i < kCount; ++i) {
                predicates[i] = false;
            }
        }

        ///< CUTLASS_HOST_DEVICE enables all accesses guarded by mask
        CUTLASS_DEVICE void enable() {
            CUTLASS_PRAGMA_UNROLL
            for (int i = 0; i < kCount; ++i) {
                predicates[i] = true;
            }
        }
    };

private:
    //
    // Data members
    //

    /// Parameters structure containing reference and precomputed state.
    PredicatedTileIteratorParams params_;

    /// Byte-level pointer
    uint8_t* byte_pointer_;

    /// Array of boolean values to contain steady-state predicates
    Mask mask_;

    /// Extent of the matrix tile in rows
    Index extent_row_;

    /// A thread's starting row position (assuming steady-state predicates have
    /// been computed)
    Index thread_start_row_;

    /// Internal state counter
    int state_[3];

private:
    //
    // Methods
    //

public:
    //
    // Methods
    //

    /// Constructor
    CUTLASS_DEVICE
    PredicatedTileIterator(PredicatedTileIteratorParams const& params,
                           Element* pointer, TensorCoord extent, int thread_idx,
                           TensorCoord threadblock_offset = TensorCoord())
            : params_(params) {
        TensorCoord thread_offset =
                ThreadMap::initial_offset(thread_idx) + threadblock_offset;

        extent_row_ = extent.row();
        thread_start_row_ = thread_offset.row();

        // Initialize predicates
        CUTLASS_PRAGMA_UNROLL
        for (int c = 0; c < ThreadMap::Iterations::kColumn; ++c) {
            mask_.predicates[c] =
                    ((thread_offset.column() + ThreadMap::Delta::kColumn * c) <
                     extent.column());
        }

        // Initialize pointer
        byte_pointer_ =
                reinterpret_cast<uint8_t*>(pointer) +
                LongIndex(thread_offset.row()) * LongIndex(params_.stride) +
                LongIndex(thread_offset.column()) * sizeof(AccessType) /
                        kElementsPerAccess;

        // Initialize internal state counter
        state_[0] = state_[1] = state_[2] = 0;
    }

    /// Adds a pointer offset in units of Element
    CUTLASS_HOST_DEVICE
    void add_pointer_offset(LongIndex pointer_offset) {
        byte_pointer_ += pointer_offset * sizeof_bits<Element>::value / 8;
    }

    /// Loads a fragment from memory
    CUTLASS_DEVICE
    void load_with_byte_offset(Fragment& frag, int64_t byte_offset) {
        uint8_t* byte_pointer = byte_pointer_;
        AccessType* frag_ptr = reinterpret_cast<AccessType*>(&frag);

        CUTLASS_PRAGMA_UNROLL
        for (int cluster = 0; cluster < ThreadMap::Iterations::kCluster;
             ++cluster) {
            CUTLASS_PRAGMA_UNROLL
            for (int group = 0; group < ThreadMap::Iterations::kGroup;
                 ++group) {
                CUTLASS_PRAGMA_UNROLL
                for (int row = 0; row < ThreadMap::Iterations::kRow; ++row) {
                    int frag_row_idx =
                            (row +
                             ThreadMap::Iterations::kRow *
                                     (group +
                                      ThreadMap::Iterations::kGroup * cluster));

                    int row_offset = row * ThreadMap::Delta::kRow +
                                     group * ThreadMap::Delta::kGroup +
                                     cluster * ThreadMap::Delta::kCluster;

                    bool row_guard =
                            ((row_offset + thread_start_row_) < extent_row_);

                    AccessType* memory_pointer = reinterpret_cast<AccessType*>(
                            byte_pointer + byte_offset);

                    CUTLASS_PRAGMA_UNROLL
                    for (int column = 0;
                         column < ThreadMap::Iterations::kColumn; ++column) {
                        bool guard = row_guard && mask_.predicates[column];

                        cutlass::arch::global_load<AccessType,
                                                   sizeof(AccessType)>(
                                frag_ptr[frag_row_idx * ThreadMap::Iterations::
                                                                kColumn +
                                         column],
                                (void*)&memory_pointer
                                        [column * ThreadMap::Delta::kColumn /
                                         kElementsPerAccess],
                                guard);
                    }

                    if (row + 1 < ThreadMap::Iterations::kRow) {
                        byte_pointer += params_.increment_row;
                    }
                }

                if (group + 1 < ThreadMap::Iterations::kGroup) {
                    byte_pointer += params_.increment_group;
                }
            }

            if (cluster + 1 < ThreadMap::Iterations::kCluster) {
                byte_pointer += params_.increment_cluster;
            }
        }
    }

    /// Loads a fragment from memory
    CUTLASS_DEVICE
    void load(Fragment& frag) { load_with_byte_offset(frag, 0); }

    /// Stores a fragment to memory
    CUTLASS_DEVICE
    void store_with_byte_offset(Fragment const& frag, int64_t byte_offset) {
        uint8_t* byte_pointer = byte_pointer_;
        AccessType const* frag_ptr = reinterpret_cast<AccessType const*>(&frag);

        CUTLASS_PRAGMA_UNROLL
        for (int cluster = 0; cluster < ThreadMap::Iterations::kCluster;
             ++cluster) {
            CUTLASS_PRAGMA_UNROLL
            for (int group = 0; group < ThreadMap::Iterations::kGroup;
                 ++group) {
                CUTLASS_PRAGMA_UNROLL
                for (int row = 0; row < ThreadMap::Iterations::kRow; ++row) {
                    int frag_row_idx =
                            (row +
                             ThreadMap::Iterations::kRow *
                                     (group +
                                      ThreadMap::Iterations::kGroup * cluster));

                    int row_offset = row * ThreadMap::Delta::kRow +
                                     group * ThreadMap::Delta::kGroup +
                                     cluster * ThreadMap::Delta::kCluster;

                    bool row_guard =
                            ((row_offset + thread_start_row_) < extent_row_);

                    AccessType* memory_pointer = reinterpret_cast<AccessType*>(
                            byte_pointer + byte_offset);

                    CUTLASS_PRAGMA_UNROLL
                    for (int column = 0;
                         column < ThreadMap::Iterations::kColumn; ++column) {
                        bool guard = row_guard && mask_.predicates[column];

                        if (guard) {
                            memory_pointer[column * ThreadMap::Delta::kColumn /
                                           kElementsPerAccess] = frag_ptr
                                    [frag_row_idx *
                                             ThreadMap::Iterations::kColumn +
                                     column];
                        }
                    }

                    if (row + 1 < ThreadMap::Iterations::kRow) {
                        byte_pointer += params_.increment_row;
                    }
                }

                if (group + 1 < ThreadMap::Iterations::kGroup) {
                    byte_pointer += params_.increment_group;
                }
            }

            if (cluster + 1 < ThreadMap::Iterations::kCluster) {
                byte_pointer += params_.increment_cluster;
            }
        }
    }

    /// Stores a fragment to memory
    CUTLASS_DEVICE
    void store(Fragment const& frag) { store_with_byte_offset(frag, 0); }

    /// Overrides the internal iteration index
    CUTLASS_HOST_DEVICE
    void set_iteration_index(int iteration) {}

    /// Advances to the next position to load or store
    CUTLASS_HOST_DEVICE
    PredicatedTileIterator& operator++() {
        ++state_[0];
        byte_pointer_ += params_.advance_row;
        thread_start_row_ += ThreadMap::Shape::kRow;

        if (state_[0] == ThreadMap::Count::kRow) {
            state_[0] = 0;
            ++state_[1];
            byte_pointer_ += params_.advance_group;

            thread_start_row_ += (ThreadMap::Shape::kGroup - 1) *
                                 ThreadMap::Shape::kRow *
                                 ThreadMap::Count::kRow;

            if (state_[1] == ThreadMap::Count::kGroup) {
                state_[1] = 0;
                ++state_[2];
                byte_pointer_ += params_.advance_cluster;

                thread_start_row_ +=
                        ThreadMap::Count::kGroup * ThreadMap::Shape::kGroup *
                        ThreadMap::Count::kRow * ThreadMap::Shape::kRow;

                if (state_[2] == ThreadMap::Count::kCluster) {
                    state_[2] = 0;
                    byte_pointer_ += params_.advance_tile;
                }
            }
        }

        return *this;
    }

    ///< Efficiently disables all accesses guarded by mask
    CUTLASS_DEVICE void clear_mask() { mask_.clear(); }

    ///< Efficiently enables all accesses guarded by mask
    CUTLASS_DEVICE void enable_mask() { mask_.enable(); }

    ///< Sets the mask
    CUTLASS_DEVICE void get_mask(Mask& mask) { return mask_; }

    ///< Sets the mask
    CUTLASS_DEVICE void set_mask(Mask const& mask) { mask_ = mask; }
};

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

/// Tile iterator used to load output tile from shared memory in epilogue.
///
/// Satisfies: ReadableTileIterator | InterleavedPredicatedTileIterator |
/// ForwardTileIterator
///
template <typename ThreadMap_,  ///< Thread map (conept: OutputTileThreadMap)
          typename Element_,    ///< Element data type
          int InterleavedN      ///< Number of Interleaved N
          >
class InterleavedPredicatedTileIterator {
public:
    using ThreadMap = ThreadMap_;

    using Element = Element_;

    using Layout = layout::ColumnMajorInterleaved<InterleavedN>;
    using TensorRef = TensorRef<Element, Layout>;
    using ConstTensorRef = typename TensorRef::ConstTensorRef;

    using Index = typename Layout::Index;
    using LongIndex = typename Layout::LongIndex;
    using TensorCoord = layout::PitchLinearCoord;

    static int const kElementsPerAccess = ThreadMap::kElementsPerAccess;
    static int const kThreads = ThreadMap::kThreads;
    static int const kIterations = ThreadMap::Iterations::kCount;

    /// Fragment object
    using Fragment = Array<Element, ThreadMap::kElementsPerAccess>;

    /// Memory access size
    using AccessType = AlignedArray<Element, ThreadMap::kElementsPerAccess>;

    //
    // Parameters struct
    //

    struct Params {
        //
        // Data members
        //

        LongIndex stride;  ///< stride in bytes between columns

        LongIndex advance_row;     ///< amount to add to move to the next 'row'
                                   ///< position
        LongIndex advance_column;  ///< amount to add to move to the next
                                   ///< 'column' position

        //
        // Methods
        //

        CUTLASS_HOST_DEVICE
        Status initialize(Index stride_) {
            stride = LongIndex(stride_);

            advance_row = ThreadMap::Delta::kContiguous *
                          sizeof_bits<Element>::value / 8;

            advance_column =
                    LongIndex(stride_) - ThreadMap::Iterations::kContiguous *
                                                 kElementsPerAccess *
                                                 sizeof_bits<Element>::value *
                                                 ThreadMap::kWarpSize / 8;

            return Status::kSuccess;
        }

        CUTLASS_HOST_DEVICE
        Params() { initialize(0); }

        CUTLASS_HOST_DEVICE
        Params(Layout const& layout) {
            initialize(layout.stride(0) * int(sizeof(AccessType)) /
                       kElementsPerAccess);
        }
    };

    /// Mask object
    struct Mask {
        static int const kCount = (ThreadMap::Iterations::kContiguous < 8)
                                          ? 8
                                          : ThreadMap::Iterations::kContiguous;

        /// Predicate state
        bool predicates[kCount];

        //
        // Mask
        //
        CUTLASS_HOST_DEVICE
        Mask() { enable(); }

        ///< Efficiently disables all accesses guarded by mask
        CUTLASS_HOST_DEVICE void clear() {
            CUTLASS_PRAGMA_UNROLL
            for (int i = 0; i < kCount; ++i) {
                predicates[i] = false;
            }
        }

        ///< CUTLASS_HOST_DEVICE enables all accesses guarded by mask
        CUTLASS_DEVICE void enable() {
            CUTLASS_PRAGMA_UNROLL
            for (int i = 0; i < kCount; ++i) {
                predicates[i] = true;
            }
        }
    };

private:
    //
    // Data members
    //

    /// Parameters structure containing reference and precomputed state.
    Params params_;

    /// Byte-level pointer
    uint8_t* byte_pointer_;

    /// Array of boolean values to contain steady-state predicates
    Mask mask_;

    /// Extent of the matrix tile in columns
    Index extent_col_;

    /// A thread's starting column position (assuming steady-state predicates
    /// have been computed)
    Index thread_start_col_;

    /// Internal iteration counter
    int iteration_contiguous_;

    int iteration_strided_;

private:
    //
    // Methods
    //

public:
    //
    // Methods
    //

    /// Constructor
    CUTLASS_DEVICE
    InterleavedPredicatedTileIterator(Params const& params, Element* pointer,
                                      TensorCoord extent, int thread_idx,
                                      TensorCoord threadblock_offset)
            : params_(params) {
        TensorCoord thread_offset =
                ThreadMap::initial_offset(thread_idx) +
                TensorCoord(threadblock_offset.contiguous() * InterleavedN,
                            threadblock_offset.strided() / InterleavedN);

        extent_col_ = extent.strided() / InterleavedN;
        thread_start_col_ = thread_offset.strided();

        // Initialize predicates
        CUTLASS_PRAGMA_UNROLL
        for (int c = 0; c < ThreadMap::Iterations::kContiguous; ++c) {
            mask_.predicates[c] = ((thread_offset.contiguous() +
                                    ThreadMap::Delta::kContiguous * c) <
                                   (extent.contiguous() * InterleavedN));
        }

        // Initialize pointer
        byte_pointer_ =
                reinterpret_cast<uint8_t*>(pointer) +
                LongIndex(thread_offset.strided()) * LongIndex(params_.stride) +
                LongIndex(thread_offset.contiguous()) * sizeof(AccessType) /
                        kElementsPerAccess;

        // Initialize internal state counter
        iteration_contiguous_ = iteration_strided_ = 0;
    }

    /// Adds a pointer offset in units of Element
    CUTLASS_HOST_DEVICE
    void add_pointer_offset(LongIndex pointer_offset) {
        byte_pointer_ += pointer_offset * sizeof_bits<Element>::value / 8;
    }

    /// Loads a fragment from memory
    CUTLASS_DEVICE
    void load(Fragment& frag) {
        uint8_t* byte_pointer = byte_pointer_;
        AccessType* frag_ptr = reinterpret_cast<AccessType*>(&frag);
        AccessType* memory_pointer =
                reinterpret_cast<AccessType*>(byte_pointer);

        int col_offset = iteration_strided_ * ThreadMap::Delta::kStrided;

        bool col_guard = ((thread_start_col_ + col_offset) < extent_col_);

        bool guard = col_guard && mask_.predicates[iteration_contiguous_];

        cutlass::arch::global_load<AccessType, sizeof(AccessType)>(
                *frag_ptr, (void*)memory_pointer, guard);
    }

    /// Stores a fragment to memory
    CUTLASS_DEVICE
    void store(Fragment const& frag) {
        uint8_t* byte_pointer = byte_pointer_;
        AccessType const* frag_ptr = reinterpret_cast<AccessType const*>(&frag);
        AccessType* memory_pointer =
                reinterpret_cast<AccessType*>(byte_pointer);

        int col_offset = iteration_strided_ * ThreadMap::Delta::kStrided;

        bool col_guard = ((thread_start_col_ + col_offset) < extent_col_);

        bool guard = col_guard && mask_.predicates[iteration_contiguous_];

        if (guard) {
            *memory_pointer = *frag_ptr;
        }
    }

    /// Overrides the internal iteration index
    CUTLASS_HOST_DEVICE
    void set_iteration_index(int iteration) {
        iteration_contiguous_ = iteration % ThreadMap::Iterations::kContiguous;
        iteration_strided_ = iteration / ThreadMap::Iterations::kContiguous;
    }

    /// Advances to the next position to load or store
    CUTLASS_HOST_DEVICE
    InterleavedPredicatedTileIterator& operator++() {
        ++iteration_contiguous_;
        byte_pointer_ += params_.advance_row;

        if (iteration_contiguous_ == ThreadMap::Iterations::kContiguous) {
            iteration_contiguous_ = 0;
            ++iteration_strided_;
            byte_pointer_ += params_.advance_column;

            if (iteration_strided_ == ThreadMap::Iterations::kStrided) {
                iteration_strided_ = 0;
            }
        }

        return *this;
    }

    ///< Efficiently disables all accesses guarded by mask
    CUTLASS_DEVICE void clear_mask() { mask_.clear(); }

    ///< Efficiently enables all accesses guarded by mask
    CUTLASS_DEVICE void enable_mask() { mask_.enable(); }

    ///< Sets the mask
    CUTLASS_DEVICE void get_mask(Mask& mask) { return mask_; }

    ///< Sets the mask
    CUTLASS_DEVICE void set_mask(Mask const& mask) { mask_ = mask; }
};

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

/// Tile iterator used to load output tile from shared memory in epilogue.
///
/// Satisfies: ReadableTileIterator | InterleavedMaskedTileIterator |
/// ForwardTileIterator
///
template <typename ThreadMap_,  ///< Thread map (conept: OutputTileThreadMap)
          typename Element_,    ///< Element data type
          int InterleavedN      ///< Number of Interleaved N
          >
class InterleavedConvPredicatedTileIterator {
public:
    using ThreadMap = ThreadMap_;

    using Element = Element_;

    using Layout = layout::TensorNCxHWx<InterleavedN>;
    using TensorRef = TensorRef<Element, Layout>;
    using ConstTensorRef = typename TensorRef::ConstTensorRef;

    using Index = typename Layout::Index;
    using LongIndex = typename Layout::LongIndex;
    using TensorCoord = Tensor4DCoord;

    static int const kElementsPerAccess = ThreadMap::kElementsPerAccess;
    static int const kThreads = ThreadMap::kThreads;
    static int const kIterations = ThreadMap::Iterations::kCount;

    /// Fragment object
    using Fragment = Array<Element, ThreadMap::kElementsPerAccess>;

    /// Memory access size
    using AccessType = AlignedArray<Element, ThreadMap::kElementsPerAccess>;

    //
    // Parameters struct
    //

    struct Params {
        //
        // Data members
        //

        LongIndex stride_col;  ///< stride in bytes between columns
        LongIndex stride_row;  ///< stride in bytes between rows

        //
        // Methods
        //

        CUTLASS_HOST_DEVICE
        Status initialize(typename Layout::Stride stride_) {
            stride_col = stride_[1];
            stride_row = stride_[2];

            return Status::kSuccess;
        }

        CUTLASS_HOST_DEVICE
        Params() { initialize(cutlass::make_Coord(0, 0, 0)); }

        CUTLASS_HOST_DEVICE
        Params(Layout const& layout) { initialize(layout.stride()); }
    };

    /// Mask object
    struct Mask {
        static int const kCount = (ThreadMap::Iterations::kRow < 8)
                                          ? 8
                                          : ThreadMap::Iterations::kRow;

        /// Predicate state
        bool predicates[kCount];

        //
        // Mask
        //
        CUTLASS_HOST_DEVICE
        Mask() { enable(); }

        ///< Efficiently disables all accesses guarded by mask
        CUTLASS_HOST_DEVICE void clear() {
            CUTLASS_PRAGMA_UNROLL
            for (int i = 0; i < kCount; ++i) {
                predicates[i] = false;
            }
        }

        ///< CUTLASS_HOST_DEVICE enables all accesses guarded by mask
        CUTLASS_DEVICE void enable() {
            CUTLASS_PRAGMA_UNROLL
            for (int i = 0; i < kCount; ++i) {
                predicates[i] = true;
            }
        }
    };

private:
    //
    // Data members
    //

    /// Parameters structure containing reference and precomputed state.
    Params params_;

    /// Byte-level pointer
    uint8_t* byte_pointer_;

    /// Array of boolean values to contain steady-state predicates
    Mask mask_;

    /// Extent of the matrix tile in columns
    Index extent_col_;

    /// Extent of the matrix tile in rows
    Index extent_row_;

    /// Extent of the matrix tile in pq
    Index extent_pq_;

    /// A thread's starting row position (assuming steady-state predicates have
    /// been computed)
    Index thread_start_row_;

    /// A thread's starting column position (assuming steady-state predicates
    /// have been computed)
    Index thread_start_col_;

    /// Internal iteration counter
    LongIndex iteration_row_;
    LongIndex iteration_col_;

    uint32_t pq_mul_;

    uint32_t pq_shr_;

private:
    //
    // Methods
    //

public:
    //
    // Methods
    //

    /// Constructor
    CUTLASS_DEVICE
    InterleavedConvPredicatedTileIterator(Params const& params,
                                          Element* pointer, TensorCoord extent,
                                          int thread_idx,
                                          MatrixCoord threadblock_offset)
            : params_(params) {
        MatrixCoord thread_offset =
                ThreadMap::initial_offset(thread_idx) + threadblock_offset;

        extent_col_ = extent.c();
        extent_pq_ = extent.h() * extent.w();
        extent_row_ = extent.n() * extent_pq_;

        find_divisor(pq_mul_, pq_shr_, extent_pq_);

        thread_start_row_ = thread_offset.row();
        thread_start_col_ = thread_offset.column();

        // Initialize predicates
        CUTLASS_PRAGMA_UNROLL
        for (int r = 0; r < ThreadMap::Iterations::kRow; ++r) {
            mask_.predicates[r] = ((thread_offset.row() +
                                    ThreadMap::Delta::kRow * r) < extent_row_);
        }

        // Initialize pointer
        byte_pointer_ =
                reinterpret_cast<uint8_t*>(pointer) +
                ((thread_start_col_ / InterleavedN) * params_.stride_col +
                 (thread_start_col_ % InterleavedN)) *
                        sizeof_bits<Element>::value / 8;

        // Initialize internal state counter
        iteration_row_ = iteration_col_ = 0;
    }

    /// Adds a pointer offset in units of Element
    CUTLASS_HOST_DEVICE
    void add_pointer_offset(LongIndex pointer_offset) {
        byte_pointer_ += pointer_offset * sizeof_bits<Element>::value / 8;
    }

    /// Loads a fragment from memory
    CUTLASS_DEVICE
    void load(Fragment& frag) {
        int col_offset = iteration_col_ * ThreadMap::Delta::kColumn;
        bool col_guard = ((thread_start_col_ + col_offset) < extent_col_);
        bool guard = col_guard && mask_.predicates[iteration_row_];

        int n, pq_rem;

        fast_divmod(n, pq_rem,
                    thread_start_row_ + iteration_row_ * ThreadMap::Delta::kRow,
                    extent_pq_, pq_mul_, pq_shr_);

        uint8_t* byte_pointer =
                byte_pointer_ +
                (n * params_.stride_row + pq_rem * InterleavedN) *
                        sizeof_bits<Element>::value / 8;
        AccessType* frag_ptr = reinterpret_cast<AccessType*>(&frag);
        AccessType const* memory_pointer =
                reinterpret_cast<AccessType const*>(byte_pointer);

        cutlass::arch::global_load<AccessType, sizeof(AccessType)>(
                *frag_ptr, (void*)memory_pointer, guard);
    }

    /// Stores a fragment to memory
    CUTLASS_DEVICE
    void store(Fragment const& frag) {
        int col_offset = iteration_col_ * ThreadMap::Delta::kColumn;
        bool col_guard = ((thread_start_col_ + col_offset) < extent_col_);
        bool guard = col_guard && mask_.predicates[iteration_row_];

        int n, pq_rem;

        fast_divmod(n, pq_rem,
                    thread_start_row_ + iteration_row_ * ThreadMap::Delta::kRow,
                    extent_pq_, pq_mul_, pq_shr_);

        uint8_t* byte_pointer =
                byte_pointer_ +
                (n * params_.stride_row + pq_rem * InterleavedN) *
                        sizeof_bits<Element>::value / 8;
        AccessType const* frag_ptr = reinterpret_cast<AccessType const*>(&frag);
        AccessType* memory_pointer =
                reinterpret_cast<AccessType*>(byte_pointer);

        if (guard) {
            *memory_pointer = *frag_ptr;
        }
    }

    /// Overrides the internal iteration index
    CUTLASS_HOST_DEVICE
    void set_iteration_index(int iteration) {
        iteration_row_ = iteration % ThreadMap::Iterations::kRow;
        iteration_col_ = iteration / ThreadMap::Iterations::kRow;
    }

    /// Advances to the next position to load or store
    CUTLASS_HOST_DEVICE
    InterleavedConvPredicatedTileIterator& operator++() {
        ++iteration_row_;

        if (iteration_row_ == ThreadMap::Iterations::kRow) {
            iteration_row_ = 0;
            ++iteration_col_;
            byte_pointer_ += params_.stride_col;

            if (iteration_col_ == ThreadMap::Iterations::kColumn) {
                iteration_col_ = 0;
            }
        }

        return *this;
    }

    ///< Efficiently disables all accesses guarded by mask
    CUTLASS_DEVICE void clear_mask() { mask_.clear(); }

    ///< Efficiently enables all accesses guarded by mask
    CUTLASS_DEVICE void enable_mask() { mask_.enable(); }

    ///< Sets the mask
    CUTLASS_DEVICE void get_mask(Mask& mask) { return mask_; }

    ///< Sets the mask
    CUTLASS_DEVICE void set_mask(Mask const& mask) { mask_ = mask; }
};

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

}  // namespace threadblock
}  // namespace epilogue
}  // namespace cutlass

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