ExtractTileOperations.cpp

#include "ExtractTileOperations.h"

#include "IRMatch.h"
#include "IRMutator.h"
#include "IROperator.h"
#include "Util.h"

/** \file Support extraction of AMX instructions. */

/**
 * https://asciiflow.com/#/share/eJyVUkFugzAQ%2FMrKxwoRhdAkza23SmlySHvogQsBp7FkbGSbAoryiz6nr%2BlLugZDk6ghKvJhbXZmd2b3QEScUbIQBece4XFNFVmQQ0SqiCwegtCLSI1RMBtjZGhl8BIRAHh%2BeoFVbBSr4Pq36ZOiSOBpX5cDCEikSGhuipjzun0pmdnD4%2BqtwX9%2Ffg2cLmUcTML76WyO4VAtWJ%2Ff7kIkWMEJ6gbBae2%2F3q53OHBuFBz3TS1HodPqfvUO3%2F4wO7gQag07IXqVkCuZU4VzyApuWI5BAJkdZ0K1B2ZP2%2BwJ%2FEs%2BjhKY0EYViWFSaMAaO6kypBY1hLCtDRIvMTvsekmlsc2kiGgKMw2cxqkGIyEGjn%2FlzonoIMjPUibeQX5Q1bHGisbav%2FBh2kHW2ESzdlaZkqUltaFd9UZ25TnIrIOg%2Bb7vQykLnv661GysRSaSF1k78HkHcaSbntSReLAtTL%2FscOlaI9rxYaRzzgwUOTrZeOCokLzN0TDqRYvUqtFwB6Fvqco9S5r%2BBCiqsWmNLHabzny2Y7E4PyJHcvwBx0t%2BJw%3D%3D)
 *
 *   LHS Matrix                           RHS Matrix
 *
 *      K                            conceptually      with AMX
 *  ┌────────┐
 *  │12345678│                             N             N*4
 *M │        │                            ┌──┐        ┌────────┐
 *  └────────┘                            │1 │     K/4│1234    │
 *                                        │2 │        │5678    │
 * To properly multiply 2 matrices, the   │3 │        └────────┘
 * AMX instructions perform many 4 byte  K│4 │
 * dot products, this leads to a lot of   │5 │
 * striding over 4 byte areas.            │6 │
 * Normally the row of the LHS matrix,    │7 │
 * 123... would multiply with the column  │8 │
 * of the RHS matrix 123..., but with AMX └──┘
 * this column is split up into a matrix of columns / 4 byte and rows * 4.
 * which then results in K/4 dot products per row.
 *
 */

namespace Halide {
namespace Internal {

using std::string;
using std::vector;

namespace {

template<int Dim>
struct Tile {
    bool result;
    Expr base;
    Expr stride[Dim];
    int extent[Dim];
};

enum class AMXOpType {
    Int8,
    Bfloat16,
};

/// returns the appropriate `Halide::Type` for the given operation type
Type amx_op_type_result_type(AMXOpType op_ty) {
    switch (op_ty) {
    case AMXOpType::Int8:
        return Int(32, 256);
    case AMXOpType::Bfloat16:
        return Float(32, 256);
    default:
        internal_error << "Unexpected";
        return Type();
    }
}

int amx_op_type_size(AMXOpType op_ty) {
    switch (op_ty) {
    case AMXOpType::Int8:
        return 1;
    case AMXOpType::Bfloat16:
        return 2;
    default:
        internal_error << "Unexpected";
        return -1;
    }
}

const auto wild_i32 = Variable::make(Int(32), "*");
const auto wild_i32x = Variable::make(Int(32, 0), "*");

Tile<1> get_1d_tile_index(const Expr &e) {
    if (const auto *r1 = e.as<Ramp>()) {
        return {true, r1->base, {r1->stride}, {r1->lanes}};
    }

    return {};
}

Tile<2> get_2d_tile_index(const Expr &e) {
    // ramp(ramp(base, 1, 4), x4(stride), 4)
    vector<Expr> matches;
    if (const auto *r1 = e.as<Ramp>()) {
        if (const auto *r2 = r1->base.as<Ramp>()) {
            auto ramp_2d_pattern = Ramp::make(Ramp::make(wild_i32, wild_i32, r2->lanes), Broadcast::make(wild_i32, r2->lanes), r1->lanes);
            if (expr_match(ramp_2d_pattern, e, matches)) {
                return {true, std::move(matches[0]), {std::move(matches[2]), std::move(matches[1])}, {r1->lanes, r2->lanes}};
            }
        }
    }
    return {};
}

Tile<3> get_3d_tile_index(const Expr &e) {
    vector<Expr> matches;

    // there could be a sub node
    const Sub *sub = e.as<Sub>();
    const Add *add = nullptr;

    if (sub) {
        add = sub->a.as<Add>();
    } else {
        add = e.as<Add>();
    }

    if (!add) {
        return {};
    }

    const auto &first = add->a;
    const auto &second = add->b;

    // ramp(x[x*r](base), x[x*r](stride), x) + x[x*y](ramp(idx, 1, r))

    const auto *r1 = first.as<Ramp>();
    const auto *b2 = second.as<Broadcast>();
    if (!r1 && !b2) {
        // Try switching the order
        r1 = second.as<Ramp>();
        b2 = first.as<Broadcast>();
    }
    if (!r1 || !b2) {
        return {};
    }

    const auto *b1 = r1->base.as<Broadcast>();
    const auto *r2 = b2->value.as<Ramp>();

    if (!b1 || !r2) {
        return {};
    }

    int x_tile = r1->lanes;
    int r_tile = r2->lanes;
    int y_tile = b1->lanes / r_tile;
    if (y_tile != b2->lanes / x_tile) {
        return {};
    }

    auto pattern1 = Ramp::make(Broadcast::make(wild_i32, b1->lanes), Broadcast::make(wild_i32, b1->lanes), r1->lanes);
    if (!expr_match(pattern1, first, matches)) {
        return {};
    }
    Expr base = std::move(matches[0]);
    Expr x_stride = std::move(matches[1]);

    auto pattern2 = Broadcast::make(Ramp::make(wild_i32, wild_i32, r2->lanes), b2->lanes);
    if (!expr_match(pattern2, second, matches)) {
        return {};
    }
    base += std::move(matches[0]);
    Expr r_stride = std::move(matches[1]);

    if (sub) {
        Expr adj = sub->b;
        const Broadcast *bcast = adj.as<Broadcast>();

        if (!bcast) {
            return {};
        }

        if (bcast->lanes != b1->lanes * r1->lanes) {
            return {};
        }

        base -= bcast->value;
    }

    return {true, base, {x_stride, 0, r_stride}, {x_tile, y_tile, r_tile}};
}

/**
 * \brief Get the 3d rhs tile index configuration
 *
 * \param e index expression
 * \param element_width the width of the elements, 1 for u8/i8, 2 for bf16
 * \return Tile<3> the tile configuration found
 *
 * The pattern which is getting matched looks roughly like
 * `broadcast(ramp(0, 1, r), x*y) / broadcast(4, x*y*r) + optional(broadcast(base, x*y*r)) * broadcast(8, x*y*r) +
 *  broadcast(ramp(0, 1, r), x*y) % broadcast(4, x*y*r) +
 *  broadcast(ramp(broadcast(_, r), broadcast(4, r), y) , x)`
 */
Tile<3> get_3d_rhs_tile_index(const Expr &e, int element_width) {
    const auto *sub = e.as<Sub>();
    const Add *add_lhs = nullptr;

    // there's not always a sub pattern
    // This depends on whether we have an ImageParam or a Buffer
    if (!sub) {
        add_lhs = e.as<Add>();
    } else {
        add_lhs = sub->a.as<Add>();
    }

    if (!add_lhs) {
        return {};
    }

    // The right hand side of the add expression is used for retrieving the dimensions of the matrix.
    // obtain the x, y, r dimensions
    // this expr looks like below, the shape of `add_lhs->a` can be seen further down below
    // broadcast(ramp(0, 1, r), x*y) % broadcast(4, x*y*r) + broadcast(ramp(broadcast(base, r), broadcast(4, r), y) , x)
    const Add *dim_expr = add_lhs->b.as<Add>();

    if (!dim_expr) {
        return {};
    }

    // broadcast(ramp(broadcast(_, r), broadcast(4, r), y), x)
    const Broadcast *base_stride_bc = dim_expr->b.as<Broadcast>();

    if (!base_stride_bc) {
        return {};
    }

    int tile_x = base_stride_bc->lanes;

    // broadcast(ramp(0, 1, r), x*y) % broadcast(4, x*y*r)
    std::vector<Expr> results{};
    const Expr mod_pattern = Mod::make(wild_i32x, Broadcast::make(4 / element_width, 0));
    if (!expr_match(mod_pattern, dim_expr->a, results)) {
        return {};
    }

    // broadcast(ramp(0, 1, r), x*y)
    const Broadcast *bc_ramp = results[0].as<Broadcast>();

    if (!bc_ramp) {
        return {};
    }

    int tile_xy = bc_ramp->lanes;
    int tile_y = tile_xy / tile_x;

    // ramp(0, 1, r)
    const Ramp *r_ramp = bc_ramp->value.as<Ramp>();

    if (!r_ramp) {
        return {};
    }

    int tile_r = r_ramp->lanes;

    // get the base and stride
    // ramp(broadcast(_, r), broadcast(4, r), y)
    const Expr base_stride_ramp_pattern = Ramp::make(Broadcast::make(wild_i32, tile_r), Broadcast::make(4 / element_width, tile_r), tile_y);
    if (!expr_match(base_stride_ramp_pattern, base_stride_bc->value, results)) {
        return {};
    }

    Expr base = results[0];
    Expr stride;

    bool found_stride = false;

    // the following pattern will match the following shape
    // broadcast(ramp(0, 1, k), x*y) / broadcast(4, x*y*k) * broadcast(_, x*y*k)
    // where the stride is marked by _.

    // this stride pattern can occur if `tile_r` is the same size as `acc`
    auto stride_pattern = Broadcast::make(Ramp::make(0, 1, tile_r), tile_x * tile_y) / Broadcast::make((4 / element_width), tile_x * tile_y * tile_r) * Broadcast::make(wild_i32, tile_x * tile_y * tile_r);

    if (expr_match(stride_pattern, add_lhs->a, results)) {
        found_stride = true;
        stride = std::move(results[0]);
    }

    // This pattern is similar to the above except with an additional offset to iterate over the tiles in the k dimension
    // (broadcast(ramp(0, 1, k), m * n) / broadcast(4, m*n*k) + _) * broadcast(_, m*n*k)
    // here the first _ marks the base and the second _ the stride.
    if (!found_stride) {
        stride_pattern = (Broadcast::make(Ramp::make(0, 1, tile_r), tile_x * tile_y) / Broadcast::make((4 / element_width), tile_x * tile_y * tile_r) + wild_i32) * Broadcast::make(wild_i32, tile_x * tile_y * tile_r);
        if (expr_match(stride_pattern, add_lhs->a, results)) {
            found_stride = true;
            stride = std::move(results[1]);
            base = std::move(results[0]) * stride + base;
        }
    }

    if (!found_stride) {
        return {};
    }

    return {true, base, {stride, 0, 0}, {tile_x, tile_y, tile_r}};
}

struct BaseStride {
    bool result{false};
    Expr base{};
    Expr stride{};
};

BaseStride get_rhs_tile_index(const Expr &index, int element_width, int tile_x, int tile_y, int tile_r) {
    const auto rhs_tile2 = get_2d_tile_index(index);

    if (!rhs_tile2.result) {
        const auto rhs_tile1 = get_1d_tile_index(index);

        if (!rhs_tile1.result) {
            auto rhs_tile3 = get_3d_rhs_tile_index(index, element_width);
            if (rhs_tile3.extent[0] != tile_x || rhs_tile3.extent[1] != tile_y || rhs_tile3.extent[2] != tile_r) {
                return {};
            }

            return {true, rhs_tile3.base, rhs_tile3.stride[0] * element_width};
        } else {
            // 1D: degenerate as dot product. There are two cases:
            //   * tile_r is 4, so effectively there is only one row in the loaded tile
            //   * rhs.stride.1 == 4 && tile_y = 1, where the loaded RHS has shape (K/4)x4
            //     and is contiguous in the memory
            if (rhs_tile1.extent[0] != tile_y * tile_r) {
                return {};
            }
            if (!(rhs_tile1.stride[0].as<IntImm>() && rhs_tile1.stride[0].as<IntImm>()->value == 1)) {
                return {};
            }

            if (tile_r == 4 / element_width) {
                return {true, rhs_tile1.base, 0};
            }

            if (tile_y == 1) {
                // 4 elements in u8/i8 and 2 elements for bf16.
                return {true, rhs_tile1.base, 4 / element_width};
            }

            return {};
        }
    } else {
        // The only case where there is a ramp of ramp is when tile_y = 1 and so RHS has size (K/4)x4
        // (and rhs.stride.1 != 4, for o.w. it degenerates to 1D)
        if (tile_y != rhs_tile2.extent[0] || tile_r != rhs_tile2.extent[1]) {
            return {};
        }
        if (!(rhs_tile2.stride[1].as<IntImm>() && rhs_tile2.stride[1].as<IntImm>()->value == 1)) {
            return {};
        }

        if (tile_y != 1) {
            return {};
        }

        return {true, rhs_tile2.base, rhs_tile2.stride[0]};
    }
}

struct Matmul {
    bool result = false;
    Stmt stmt;
    int tile_x;
    int tile_y;
    int tile_r;
};

Matmul convert_to_matmul(const Store *op, const string &new_name, AMXOpType op_type) {
    // m[ramp(0, 1, S)] = VectorAdd(lhs[{XYR tile}] * xX(rhs[{YR tile}])) + m[ramp(0, 1, S)]
    const auto wild_i8x = Variable::make(Int(8, 0), "*");
    const auto wild_u8x = Variable::make(UInt(8, 0), "*");
    const auto wild_bf16x = Variable::make(BFloat(16, 0), "*");
    const auto wild_f32x = Variable::make(Float(32, 0), "*");

    vector<Expr> matches;
    if (op_type == AMXOpType::Int8) {
        const auto pattern1 = wild_i32x + wild_i32x;
        if (!expr_match(pattern1, op->value, matches)) {
            return {};
        }
    } else {  // AMXOpType::Bfloat16
        const auto pattern1 = wild_f32x + wild_f32x;
        if (!expr_match(pattern1, op->value, matches)) {
            return {};
        }
    }

    const auto *reduce = matches[0].as<VectorReduce>();
    const auto *load = matches[1].as<Load>();
    if (!reduce || reduce->op != VectorReduce::Add) {
        return {};
    }
    if (!load || load->name != op->name || !equal(load->index, op->index)) {
        return {};
    }

    if (op_type == AMXOpType::Int8) {
        auto pattern2 = cast(Int(32, 0), cast(Int(32, 0), wild_i8x) * wild_i32x);
        auto pattern2_unsigned = cast(Int(32, 0), cast(Int(32, 0), wild_u8x) * wild_i32x);

        if (!(expr_match(pattern2, reduce->value, matches) || expr_match(pattern2_unsigned, reduce->value, matches))) {
            return {};
        }
    } else {
        auto pattern2 = cast(Float(32, 0), cast(Float(32, 0), wild_bf16x) * wild_f32x);

        if (!expr_match(pattern2, reduce->value, matches)) {
            return {};
        }
    }

    const auto *lhs_load = matches[0].as<Load>();
    const auto *rhs_broadcast = matches[1].as<Broadcast>();

    const Cast *rhs_cast = nullptr;

    if (lhs_load && !rhs_broadcast) {
        // now working on a larger k dimension
        // with a K dimension of 4 (or 2) with bf16 all the elements in the right-hand matrix are
        // layed out in a way that multiplying with a column can be done in a single dot product.
        // Therefore the indexing can be reused with a broadcast,
        // with higher K dimensions this can no longer be done and the broadcast won't exist.
        // ┌──┐
        // │1 │
        // │2 │
        // │3 │   ┌────────┐
        // │4 │   │1234    │
        // │5 │   │5678    │
        // │6 │   └────────┘
        // │7 │
        // │8 │
        // └──┘
        rhs_cast = matches[1].as<Cast>();
    } else {
        rhs_cast = rhs_broadcast->value.as<Cast>();
    }

    if (!lhs_load || !rhs_cast) {
        return {};
    }

    if (rhs_cast) {
        bool is_i8_u8 = rhs_cast->value.type().element_of() == Int(8) || rhs_cast->value.type().element_of() == UInt(8);
        bool is_bf16 = rhs_cast->value.type().element_of() == BFloat(16);

        if ((op_type == AMXOpType::Int8 && !is_i8_u8) || (op_type == AMXOpType::Bfloat16 && !is_bf16)) {
            user_error << "Expected rhs type of " << (op_type == AMXOpType::Int8 ? "i8/u8" : "bf16")
                       << ", got " << rhs_cast->value.type() << " instead.\nIn Expression: " << Expr(rhs_cast);
        }
    } else {
        return {};
    }

    const auto *rhs_load = rhs_cast->value.as<Load>();
    if (!rhs_load) {
        return {};
    }

    const auto lhs_tile = get_3d_tile_index(lhs_load->index);

    if (!lhs_tile.result) {
        return {};
    }

    const int tile_x = lhs_tile.extent[0];
    const int tile_y = lhs_tile.extent[1];
    const int tile_r = lhs_tile.extent[2];
    const int factor = reduce->value.type().lanes() / reduce->type.lanes();

    Expr rhs_base;
    Expr rhs_stride;

    auto opt_base_stride = get_rhs_tile_index(rhs_load->index, amx_op_type_size(op_type), tile_x, tile_y, tile_r);

    if (!opt_base_stride.result) {
        return {};
    }

    rhs_base = opt_base_stride.base;
    rhs_stride = opt_base_stride.stride;

    if (op->index.type().lanes() != tile_x * tile_y ||
        factor != tile_r) {
        return {};
    }

    // {rows, colbytes, var, index}
    auto lhs_var = Variable::make(Handle(), lhs_load->name);
    const auto &lhs_load_type = lhs_load->type;
    int element_width = lhs_load_type.bytes();
    auto lhs_type = lhs_load_type.with_lanes(1024 / element_width);
    auto lhs = Call::make(lhs_type, "tile_load", {tile_x, tile_r * element_width, lhs_var, lhs_tile.base * element_width, lhs_tile.stride[0] * element_width}, Call::Intrinsic);

    auto rhs_var = Variable::make(Handle(), rhs_load->name);
    const auto &rhs_load_type = rhs_load->type;
    auto rhs_type = rhs_load_type.with_lanes(1024 / element_width);

    auto rhs = Call::make(rhs_type, "tile_load", {tile_r / (4 / element_width), tile_y * 4, rhs_var, rhs_base * element_width, rhs_stride}, Call::Intrinsic);
    auto res_type = amx_op_type_result_type(op_type);

    // {rows, colbytes, acc, out, lhs, rhs}
    auto out = Load::make(res_type, new_name, Ramp::make(0, 1, 256), {}, {}, const_true(256), {});

    // 4 bytes for i32, f32
    auto colbytes = tile_y * 4;
    auto matmul = Call::make(res_type, "tile_matmul", {tile_x, colbytes, tile_r, out, lhs, rhs}, Call::Intrinsic);
    auto store = Store::make(new_name, matmul, Ramp::make(0, 1, 256), Parameter(), const_true(256), ModulusRemainder());
    return {true, std::move(store), tile_x, tile_y, tile_r};
}

Stmt convert_to_zero(const Store *op, int tile_x, int tile_y, const string &new_name) {
    if (const auto *ramp = op->index.as<Ramp>()) {
        if (const auto *bcast = op->value.as<Broadcast>()) {
            if (is_const_one(ramp->stride) &&
                is_const_zero(bcast->value) &&
                (bcast->lanes == tile_x * tile_y)) {
                auto rows = Cast::make(Int(16), tile_x);
                auto bytes = op->value.type().bytes();
                auto colbytes = Cast::make(Int(16), tile_y * bytes);
                const auto &store_type = op->value.type();
                // will be f32 or i32
                auto tile_zero_type = store_type.with_lanes(1024 / store_type.bytes());
                auto val = Call::make(tile_zero_type, "tile_zero", {rows, colbytes}, Call::Intrinsic);
                auto store = Store::make(new_name, std::move(val), Ramp::make(0, 1, 256), Parameter(), const_true(256), ModulusRemainder());
                return store;
            }
        }
    }
    return {};
}

Stmt convert_to_tile_store(const Store *op, const string &amx_name, int tile_x, int tile_y) {
    auto tile = get_2d_tile_index(op->index);
    if (tile.result && tile.extent[0] == tile_x && tile.extent[1] == tile_y) {
        auto out = Variable::make(Handle(), op->name);
        auto tile_type = op->value.type().with_lanes(256);
        auto tile_val = Load::make(tile_type, amx_name, Ramp::make(0, 1, 256), {}, {}, const_true(256), {});
        auto bytes = op->value.type().bytes();
        internal_assert(bytes == 4) << "AMX store only supported for int32 and float32 output, not for " << op->value.type() << "\n";
        // {tile_x, tile_y, var, base, stride}
        auto store = Call::make(Int(32), "tile_store", {tile_x, tile_y * bytes, std::move(out), tile.base * bytes, tile.stride[0] * bytes, std::move(tile_val)}, Call::Intrinsic);
        return Evaluate::make(std::move(store));
    }
    return {};
}

class ExtractTileOperations : public IRMutator {
    using IRMutator::visit;

    string tile_name;
    string amx_name;
    vector<Stmt> pending_stores;
    bool in_allocate = false;
    int found_tile_x = -1;
    int found_tile_y = -1;
    int found_tile_r = -1;
    AMXOpType op_type;

    Stmt visit(const Allocate *op) override {
        if (op->memory_type == MemoryType::AMXTile) {
            user_assert(
                (op->type.is_int() && op->type.bits() == 32) ||
                (op->type.is_float() && op->type.bits() == 32))
                << "scheduled tile operations must yield 32-bit integers or 32-bit floats";

            if (op->type.is_int() && op->type.bits() == 32) {
                op_type = AMXOpType::Int8;
            } else {
                op_type = AMXOpType::Bfloat16;
            }

            user_assert(!in_allocate) << "Already in AMX allocation: " << amx_name;
            ScopedValue<string> old_amx_name(amx_name, op->name + ".amx");
            ScopedValue<string> old_tile_name(tile_name, op->name);
            ScopedValue<bool> old_in_alloc(in_allocate, true);
            Stmt body = op->body;

            pending_stores.clear();
            body = mutate(body);
            if (found_tile_x < 0 || found_tile_y < 0 || found_tile_r < 0) {
                return op;
            }
            if (!pending_stores.empty()) {
                // Really only need to go over the pending stores
                body = mutate(body);
            }

            auto alloc_type = amx_op_type_result_type(op_type);
            return Allocate::make(amx_name, alloc_type, MemoryType::AMXTile, {1}, const_true(), body);
        }
        return IRMutator::visit(op);
    }

    Stmt visit(const Free *op) override {
        if (op->name != tile_name) {
            return op;
        }
        return Free::make(amx_name);
    }

    Stmt visit(const ProducerConsumer *op) override {
        if (op->name != tile_name) {
            return IRMutator::visit(op);
        }

        auto body = mutate(op->body);
        return ProducerConsumer::make(amx_name, op->is_producer, std::move(body));
    }

    Expr visit(const Load *op) override {
        // Any tile load will be matched elsewhere, so a load here means that
        // the AMX tile is used outside of a tile instruction.
        user_assert(op->name != tile_name) << "AMX tile allocation used outside a tile instruction";
        return IRMutator::visit(op);
    }

    Stmt visit(const Store *op) override {
        if (op->name != tile_name) {
            const auto *load = op->value.as<Load>();
            if (!load || load->name != tile_name) {
                return op;
            }
            auto store = convert_to_tile_store(op, amx_name, found_tile_x, found_tile_y);
            user_assert(store.defined()) << "Store to AMX tile allocation of a non-tile value";
            return store;
        }

        auto matmul = convert_to_matmul(op, amx_name, op_type);
        if (matmul.result) {
            user_assert(
                (found_tile_x < 0 || matmul.tile_x == found_tile_x) &&
                (found_tile_y < 0 || matmul.tile_y == found_tile_y) &&
                (found_tile_r < 0 || matmul.tile_r == found_tile_r))
                << "Found different tile sizes for AMX tile allocation";
            found_tile_x = matmul.tile_x;
            found_tile_y = matmul.tile_y;
            found_tile_r = matmul.tile_r;

            return matmul.stmt;
        }

        if (found_tile_x < 0 || found_tile_y < 0) {
            pending_stores.emplace_back(op);
            return op;
        }

        auto zero = convert_to_zero(op, found_tile_x, found_tile_y, amx_name);
        if (zero.defined()) {
            return zero;
        }

        // Otherwise there is some other operation using the allocation, so we cannot use the AMX instructions
        user_error << "Found non-tile operations for AMX tile allocation";
        return op;
    }
};

}  // namespace

Stmt extract_tile_operations(const Stmt &s) {
    return ExtractTileOperations().mutate(s);
}
}  // namespace Internal
}  // namespace Halide