julia> @finch_code begin
        y .= 0
        for j = parallel(_)
            for i = _
                y[j] += x[i] * A[walk(i), j]
            end
        end
    end
quote
    y_lvl = (ex.bodies[1]).tns.bind.lvl
    y_lvl_2 = y_lvl.lvl
    x_lvl = ((ex.bodies[2]).body.body.rhs.args[1]).tns.bind.lvl
    x_lvl_2 = x_lvl.lvl
    A_lvl = ((ex.bodies[2]).body.body.rhs.args[2]).tns.bind.lvl
    A_lvl_2 = A_lvl.lvl
    A_lvl_3 = A_lvl_2.lvl
    A_lvl_2.shape == x_lvl.shape || throw(DimensionMismatch("mismatched dimension limits ($(A_lvl_2.shape) != $(x_lvl.shape))"))
    Finch.resize_if_smaller!(y_lvl_2.val, A_lvl.shape)
    Finch.fill_range!(y_lvl_2.val, 0.0, 1, A_lvl.shape)
    Threads.@threads for i_4 = 1:Threads.nthreads()
            phase_start_2 = max(1, 1 + fld(A_lvl.shape * (i_4 + -1), Threads.nthreads()))
            phase_stop_2 = min(A_lvl.shape, fld(A_lvl.shape * i_4, Threads.nthreads()))
            if phase_stop_2 >= phase_start_2
                for j_6 = phase_start_2:phase_stop_2
                    y_lvl_q = (1 - 1) * A_lvl.shape + j_6
                    A_lvl_q = (1 - 1) * A_lvl.shape + j_6
                    A_lvl_2_q = A_lvl_2.ptr[A_lvl_q]
                    A_lvl_2_q_stop = A_lvl_2.ptr[A_lvl_q + 1]
                    if A_lvl_2_q < A_lvl_2_q_stop
                        A_lvl_2_i1 = A_lvl_2.idx[A_lvl_2_q_stop - 1]
                    else
                        A_lvl_2_i1 = 0
                    end
                    phase_stop_3 = min(A_lvl_2.shape, A_lvl_2_i1)
                    if phase_stop_3 >= 1
                        i = 1
                        if A_lvl_2.idx[A_lvl_2_q] < 1
                            A_lvl_2_q = Finch.scansearch(A_lvl_2.idx, 1, A_lvl_2_q, A_lvl_2_q_stop - 1)
                        end
                        while i <= phase_stop_3
                            A_lvl_2_i = A_lvl_2.idx[A_lvl_2_q]
                            phase_stop_4 = min(phase_stop_3, A_lvl_2_i)
                            if A_lvl_2_i == phase_stop_4
                                A_lvl_3_val_2 = A_lvl_3.val[A_lvl_2_q]
                                x_lvl_q = (1 - 1) * x_lvl.shape + phase_stop_4
                                x_lvl_2_val_2 = x_lvl_2.val[x_lvl_q]
                                y_lvl_2.val[y_lvl_q] = y_lvl_2.val[y_lvl_q] + A_lvl_3_val_2 * x_lvl_2_val_2
                                A_lvl_2_q += 1
                            end
                            i = phase_stop_4 + 1
                        end
                    end
                end
            end
        end
    qos = 1 * A_lvl.shape
    resize!(y_lvl_2.val, qos)
    (y = Fiber((DenseLevel){Int32}(y_lvl_2, A_lvl.shape)),)
end
julia> @finch begin
        y .= 0
        for j = parallel(_)
            for i = _
                y[j] += x[i] * A[walk(i), j]
            end
        end
    end
(y = Fiber(Dense{Int32}(Element{0.0, Float64, Int32, Vector{Float64}}([4.0, 6.0]), 2)),)

