begin
    y_lvl = ((ex.bodies[1]).bodies[1]).tns.bind.lvl
    y_lvl_2 = y_lvl.lvl
    y_lvl_val = y_lvl.lvl.val
    x_lvl = (((ex.bodies[1]).bodies[2]).body.body.rhs.args[1]).tns.bind.lvl
    x_lvl_val = x_lvl.lvl.val
    A_lvl = (((ex.bodies[1]).bodies[2]).body.body.rhs.args[2]).tns.bind.lvl
    A_lvl_2 = A_lvl.lvl
    A_lvl_ptr = A_lvl_2.ptr
    A_lvl_idx = A_lvl_2.idx
    A_lvl_2_val = A_lvl_2.lvl.val
    A_lvl_2.shape == x_lvl.shape || throw(DimensionMismatch("mismatched dimension limits ($(A_lvl_2.shape) != $(x_lvl.shape))"))
    result = nothing
    Finch.resize_if_smaller!(y_lvl_val, A_lvl.shape)
    Finch.fill_range!(y_lvl_val, 0.0, 1, A_lvl.shape)
    val = y_lvl_val
    y_lvl_val = (Finch).moveto(y_lvl_val, CPU(Threads.nthreads()))
    A_lvl_ptr = (Finch).moveto(A_lvl_ptr, CPU(Threads.nthreads()))
    A_lvl_idx = (Finch).moveto(A_lvl_idx, CPU(Threads.nthreads()))
    A_lvl_2_val = (Finch).moveto(A_lvl_2_val, CPU(Threads.nthreads()))
    x_lvl_val = (Finch).moveto(x_lvl_val, CPU(Threads.nthreads()))
    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_ptr[A_lvl_q]
                    A_lvl_2_q_stop = A_lvl_ptr[A_lvl_q + 1]
                    if A_lvl_2_q < A_lvl_2_q_stop
                        A_lvl_2_i1 = A_lvl_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
                        if A_lvl_idx[A_lvl_2_q] < 1
                            A_lvl_2_q = Finch.scansearch(A_lvl_idx, 1, A_lvl_2_q, A_lvl_2_q_stop - 1)
                        end
                        while true
                            A_lvl_2_i = A_lvl_idx[A_lvl_2_q]
                            if A_lvl_2_i < phase_stop_3
                                A_lvl_3_val = A_lvl_2_val[A_lvl_2_q]
                                x_lvl_q = (1 - 1) * x_lvl.shape + A_lvl_2_i
                                x_lvl_2_val = x_lvl_val[x_lvl_q]
                                y_lvl_val[y_lvl_q] += A_lvl_3_val * x_lvl_2_val
                                A_lvl_2_q += 1
                            else
                                phase_stop_5 = min(A_lvl_2_i, phase_stop_3)
                                if A_lvl_2_i == phase_stop_5
                                    A_lvl_3_val = A_lvl_2_val[A_lvl_2_q]
                                    x_lvl_q = (1 - 1) * x_lvl.shape + phase_stop_5
                                    x_lvl_2_val_2 = x_lvl_val[x_lvl_q]
                                    y_lvl_val[y_lvl_q] += A_lvl_3_val * x_lvl_2_val_2
                                    A_lvl_2_q += 1
                                end
                                break
                            end
                        end
                    end
                end
            end
        end
    resize!(val, A_lvl.shape)
    result = (y = Tensor((DenseLevel){Int32}(y_lvl_2, A_lvl.shape)),)
    result
end
