def __init__(self, # host_halo=halo.HALOS,
occ_matrix=cuda_cell.OCCUPANCY_MATRIX):
# self._host_halo_handle = host_halo
self._occ_matrix = occ_matrix
self._version = -1
self._init = False
# vars init
self._boundary_cell_groups = cuda_base.Array(dtype=ctypes.c_int)
self._boundary_groups_start_end_indices = cuda_base.Array(ncomp=27, dtype=ctypes.c_int)
self._halo_cell_groups = cuda_base.Array(dtype=ctypes.c_int)
self._halo_groups_start_end_indices = cuda_base.Array(ncomp=27, dtype=ctypes.c_int)
self._boundary_groups_contents_array = cuda_base.Array(dtype=ctypes.c_int)
self._exchange_sizes = cuda_base.Array(ncomp=26, dtype=ctypes.c_int)
self._halo_shifts = None
self._reverse_lookup = None
# ensure first update
self._boundary_cell_groups.inc_version(-1)
self._boundary_groups_start_end_indices.inc_version(-1)
self._halo_cell_groups.inc_version(-1)
self._halo_groups_start_end_indices.inc_version(-1)
self._boundary_groups_contents_array.inc_version(-1)
self._exchange_sizes.inc_version(-1)
def _cell_sort_setup(self):
self.particle_layers = cuda_base.Array(ncomp=self._n_func(),
dtype=ctypes.c_int)
self.cell_reverse_lookup = cuda_base.Array(ncomp=self._n_func(),
dtype=ctypes.c_int)
self.cell_contents_count = cuda_base.Array(
ncomp=self._domain.cell_count, dtype=ctypes.c_int)
self.matrix = cuda_base.device_buffer_2d(nrow=self._domain.cell_count,
ncol=self._n_func() //
self._domain.cell_count,
dtype=ctypes.c_int)
self._n_layers = self.matrix.ncol
self._n_cells = self.matrix.nrow
#self._boundary = cuda_base.Array(initial_value=self._domain.boundary_outer)
#self._cell_edge_lengths = cuda_base.Array(initial_value=self._domain.cell_edge_lengths)
#self._cell_array = cuda_base.Array(initial_value=self._domain.cell_array, dtype=ctypes.c_int)
self._setup = True
self._build()
def __init__(self):
self._init = False
self._setup = False
self.cell_contents_count = None
"""Number of particles per cell, determines number of layers per cell."""
self.cell_reverse_lookup = None
"""Map between particle index and containing cell."""
self.particle_layers = None
"""Stores which layer each particle is contained in."""
self.matrix = None
"""The occupancy matrix."""
# build vars
self._p1_lib = None
self._boundary = None
self._cell_edge_lengths = None
self._cell_array = None
self.cell_in_halo_flag = None
# setup vars
self._n_func = None
self._domain = None
self._positions = None
self._n_layers = 0
self.update_required = True
self._update_set = False
self._update_func = None
self._update_func_pre = None
self._update_func_post = None
self.version_id = 0
self.version_id_halo = 0
self._timer = ppmd.opt.Timer()
# scan vars
self._ccc_scan = cuda_base.Array(ncomp=1, dtype=ctypes.c_int)
def __init__(self, state_in=None):
self.state = state_in
# Initialise timers
self.timer_apply = ppmd.opt.Timer(cuda_runtime.TIMER, 0)
self.timer_lib_overhead = ppmd.opt.Timer(cuda_runtime.TIMER, 0)
self.timer_search = ppmd.opt.Timer(cuda_runtime.TIMER, 0)
self.timer_move = ppmd.opt.Timer(cuda_runtime.TIMER, 0)
# One proc PBC lib
self._one_process_pbc_lib = None
# Escape guard lib
self._escape_guard_lib = None
self._escape_count = None
self._escape_dir_count = None
self._escape_list = None
self._escape_matrix = None
self._flag = cuda_base.Array(ncomp=1, dtype=ctypes.c_int)
def _update_cell_in_halo(self):
if self._cell_array is None or \
self._cell_array[0] != self._domain.cell_array[0] or \
self._cell_array[1] != self._domain.cell_array[1] or \
self._cell_array[2] != self._domain.cell_array[2]:
# --
self._cell_array = np.array(self._domain.cell_array[:])
tl = self._cell_array[0] * self._cell_array[1] * self._cell_array[2]
ca = self._cell_array
tmp = np.ones((ca[2], ca[1], ca[0]), dtype=ctypes.c_int)
tmp[1:ca[2] - 1:, 1:ca[1] - 1:, 1:ca[0] - 1:] = 0
tmp[2:ca[2] - 2:, 2:ca[1] - 2:, 2:ca[0] - 2:] = -1
tmp = tmp.ravel()
self.cell_in_halo_flag = cuda_base.Array(ncomp=tl,
dtype=ctypes.c_int)
self.cell_in_halo_flag[:] = tmp
def _get_pairs(self):
_cell_pairs = (
create_halo_pairs(self.occ_matrix.domain, Slice[0,0,0],(-1,-1,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[::,0,0],(0,-1,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,0,0],(1,-1,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[0,::,0],(-1,0,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[::,::,0],(0,0,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,::,0],(1,0,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[0,-1,0],(-1,1,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[::,-1,0],(0,1,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,-1,0],(1,1,-1)),
create_halo_pairs(self.occ_matrix.domain, Slice[0,0,::],(-1,-1,0)),
create_halo_pairs(self.occ_matrix.domain, Slice[::,0,::],(0,-1,0)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,0,::],(1,-1,0)),
create_halo_pairs(self.occ_matrix.domain, Slice[0,::,::],(-1,0,0)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,::,::],(1,0,0)),
create_halo_pairs(self.occ_matrix.domain, Slice[0,-1,::],(-1,1,0)),
create_halo_pairs(self.occ_matrix.domain, Slice[::,-1,::],(0,1,0)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,-1,::],(1,1,0)),
create_halo_pairs(self.occ_matrix.domain, Slice[0,0,-1],(-1,-1,1)),
create_halo_pairs(self.occ_matrix.domain, Slice[::,0,-1],(0,-1,1)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,0,-1],(1,-1,1)),
create_halo_pairs(self.occ_matrix.domain, Slice[0,::,-1],(-1,0,1)),
create_halo_pairs(self.occ_matrix.domain, Slice[::,::,-1],(0,0,1)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,::,-1],(1,0,1)),
create_halo_pairs(self.occ_matrix.domain, Slice[0,-1,-1],(-1,1,1)),
create_halo_pairs(self.occ_matrix.domain, Slice[::,-1,-1],(0,1,1)),
create_halo_pairs(self.occ_matrix.domain, Slice[-1,-1,-1],(1,1,1))
)
_bs = np.zeros(1, dtype=ctypes.c_int)
_b = np.zeros(0, dtype=ctypes.c_int)
_hs = np.zeros(1, dtype=ctypes.c_int)
_h = np.zeros(0, dtype=ctypes.c_int)
_s = np.zeros(0, dtype=ctypes.c_double)
_r = np.zeros(0, dtype=ctypes.c_int)
for hx, bhx in enumerate(_cell_pairs):
# Boundary and Halo start index.
_bs = np.append(_bs, ctypes.c_int(len(bhx[0])))
_hs = np.append(_hs, ctypes.c_int(len(bhx[1])))
# Actual cell indices
_b = np.append(_b, bhx[0])
_h = np.append(_h, bhx[1])
# Offset shifts for periodic boundary
_s = np.append(_s, bhx[2])
# reverse lookup required for cuda.
_r = np.append(_r, np.array(hx * np.ones(len(bhx[0])), dtype=ctypes.c_int))
self._boundary_groups_start_end_indices = cuda_base.Array(_bs, dtype=ctypes.c_int)
self._halo_groups_start_end_indices = cuda_base.Array(_hs, dtype=ctypes.c_int)
# print "CA =", self.occ_matrix.domain.cell_array
# print _b
self._boundary_cell_groups = cuda_base.Array(_b, dtype=ctypes.c_int)
self._halo_cell_groups = cuda_base.Array(_h, dtype=ctypes.c_int)
# print "SHIFTS"
self._halo_shifts = cuda_base.Array(_s, dtype=ctypes.c_double)
# print "E_SHIFTS", self._halo_shifts.ctypes_data
self._reverse_lookup = cuda_base.Array(_r, dtype=ctypes.c_int)
self._version = self._occ_matrix.domain.cell_array.version
def __init__(self, domain, cell_width, positions):
self.domain = domain
boundary = domain.boundary
assert cell_width > 0, "bad cell width"
assert boundary[1] > boundary[0], "nonsensical boundary"
assert boundary[3] > boundary[2], "nonsensical boundary"
assert boundary[5] > boundary[4], "nonsensical boundary"
self.positions = positions
self.cell_array = host.Array(ncomp=3, dtype=ctypes.c_int)
self.cell_sizes = host.Array(ncomp=3, dtype=ctypes.c_double)
# get sizes just considering interior
cell_array = [0, 0, 0]
cell_array[0] = int(float(boundary[1] - boundary[0]) / cell_width)
cell_array[1] = int(float(boundary[3] - boundary[2]) / cell_width)
cell_array[2] = int(float(boundary[5] - boundary[4]) / cell_width)
cell_sizes = [0, 0, 0]
cell_sizes[0] = float(boundary[1] - boundary[0]) / cell_array[0]
cell_sizes[1] = float(boundary[3] - boundary[2]) / cell_array[1]
cell_sizes[2] = float(boundary[5] - boundary[4]) / cell_array[2]
self.cell_sizes[:] = cell_sizes[:]
padx = int(math.ceil(
self.domain.cell_edge_lengths[0] / cell_sizes[0])) + 1
pady = int(math.ceil(
self.domain.cell_edge_lengths[1] / cell_sizes[1])) + 1
padz = int(math.ceil(
self.domain.cell_edge_lengths[2] / cell_sizes[2])) + 1
rpadx = padx * cell_sizes[0]
rpady = pady * cell_sizes[1]
rpadz = padz * cell_sizes[2]
#print "CA", cell_array[:], "CS", self.cell_sizes[:], "CES", self.domain.cell_edge_lengths[:]
self.cell_array[0] = cell_array[0] + 2 * padx
self.cell_array[1] = cell_array[1] + 2 * pady
self.cell_array[2] = cell_array[2] + 2 * padz
#print "CA2", self.cell_array[:]
self.boundary = host.Array(ncomp=6, dtype=ctypes.c_double)
self.boundary[0] = boundary[0] - rpadx
self.boundary[1] = boundary[1] + rpadx
self.boundary[2] = boundary[2] - rpady
self.boundary[3] = boundary[3] + rpady
self.boundary[4] = boundary[4] - rpadz
self.boundary[5] = boundary[5] + rpadz
self.cell_count = cell_array[0] * cell_array[1] * cell_array[2]
self.particle_layers = cuda_base.Array(ncomp=1, dtype=ctypes.c_int)
self.cell_reverse_lookup = cuda_base.Array(ncomp=1, dtype=ctypes.c_int)
self.cell_contents_count = cuda_base.Array(ncomp=self.cell_count,
dtype=ctypes.c_int)
self.matrix = cuda_base.Matrix(nrow=self.cell_count,
ncol=1,
dtype=ctypes.c_int)
self.num_layers = 0
with open(
str(ppmd.cuda.cuda_config.LIB_DIR) +
'/cudaSubCellOccupancyMatrixSource.cu', 'r') as fh:
_code = fh.read()
with open(
str(ppmd.cuda.cuda_config.LIB_DIR) +
'/cudaSubCellOccupancyMatrixSource.h', 'r') as fh:
_header = fh.read()
_name = 'SubCellOccupancyMatrix'
lib = cuda_build.simple_lib_creator(_header, _code, _name)
self._sort_lib = lib['LayerSort']
self._fill_lib = lib['PopMatrix']
self.version_id = 0
def apply(self):
"""
Enforce the boundary conditions on the held state.
"""
comm = self.state.domain.comm
self.timer_apply.start()
if comm.Get_size() == 1:
"""
BC code for one proc. porbably removable when restricting to large
parallel systems.
"""
self.timer_lib_overhead.start()
if self._one_process_pbc_lib is None:
with open(
str(cuda_config.LIB_DIR) + '/cudaOneProcPBCSource.cu',
'r') as fh:
_one_proc_pbc_code = fh.read()
_one_proc_pbc_kernel = kernel.Kernel('_one_proc_pbc_kernel',
_one_proc_pbc_code,
None,
static_args={
'E0': ctypes.c_double,
'E1': ctypes.c_double,
'E2': ctypes.c_double
})
self._one_process_pbc_lib = cuda_loop.ParticleLoop(
_one_proc_pbc_kernel, {
'P': self.state.get_position_dat()(access.RW),
'BCFLAG': self._flag(access.INC_ZERO)
})
self.timer_lib_overhead.pause()
_E = self.state.domain.extent
self.timer_move.start()
self._one_process_pbc_lib.execute(
n=self.state.get_position_dat().npart_local,
static_args={
'E0': ctypes.c_double(_E[0]),
'E1': ctypes.c_double(_E[1]),
'E2': ctypes.c_double(_E[2])
})
res = self._flag[0]
if res > 0:
self._flag[0] = 1
self.timer_move.pause()
############ ----- MULTIPROC -------
else:
if self._escape_guard_lib is None:
# build lib
self._escape_guard_lib = \
cuda_build.build_static_libs('cudaNProcPBC')
# --- init escape count ----
if self._escape_count is None:
self._escape_count = cuda_base.Array(ncomp=1,
dtype=ctypes.c_int32)
self._escape_count[0] = 0
# --- init escape dir count ----
if self._escape_dir_count is None:
self._escape_dir_count = cuda_base.Array(ncomp=26,
dtype=ctypes.c_int32)
self._escape_dir_count[:] = 0
# --- init escape list ----
nl3 = self.state.get_position_dat().npart_local * 3
if self._escape_list is None:
self._escape_list = cuda_base.Array(ncomp=nl3,
dtype=ctypes.c_int32)
elif self._escape_list.ncomp < nl3:
self._escape_list.realloc(nl3)
# --- find escapees ---
nl = self.state.get_position_dat().npart_local
if nl > 0:
cuda_runtime.cuda_err_check(
self._escape_guard_lib['cudaNProcPBCStageOne'](
ctypes.c_int32(nl),
self.state.domain.boundary.ctypes_data,
self.state.get_position_dat().ctypes_data,
self.state.domain.get_shift().ctypes_data,
self._escape_count.ctypes_data,
self._escape_dir_count.ctypes_data,
self._escape_list.ctypes_data))
dir_max = np.max(self._escape_dir_count[:]) + 1
if self._escape_matrix is None:
self._escape_matrix = cuda_base.Matrix(nrow=26,
ncol=dir_max,
dtype=ctypes.c_int32)
elif self._escape_matrix.ncol < dir_max:
self._escape_matrix.realloc(nrow=26, ncol=dir_max)
# --- Populate escape matrix (essentially sort by direction)
escape_count = self._escape_count[0]
if (nl > 0) and (escape_count > 0):
cuda_runtime.cuda_err_check(
self._escape_guard_lib['cudaNProcPBCStageTwo'](
ctypes.c_int32(escape_count),
ctypes.c_int32(self._escape_matrix.ncol),
self._escape_list.ctypes_data,
self._escape_matrix.ctypes_data))
self.state.move_to_neighbour(directions_matrix=self._escape_matrix,
dir_counts=self._escape_dir_count)
self.state.filter_on_domain_boundary()
def __init__(self, kernel=None, dat_dict=None, shell_cutoff=None, sub_divide=None):
self._dat_dict = access.DatArgStore(
self._get_allowed_types(), dat_dict)
self._cc = cuda_build.NVCC
self._kernel = kernel
self.shell_cutoff = shell_cutoff
if sub_divide is None:
rs_default = 5.
else:
rs_default = sub_divide
self.sub_divide_size = rs_default
#print "ACTUAL SUB CELL WIDTH", self.sub_divide_size
self.loop_timer = ppmd.modules.code_timer.LoopTimer()
self.wrapper_timer = opt.SynchronizedTimer(runtime.TIMER)
self._components = {'LIB_PAIR_INDEX_0': '_i',
'LIB_PAIR_INDEX_1': '_j',
'LIB_NAME': str(self._kernel.name) + '_wrapper'}
self._gather_size_limit = 4
self._generate()
self._lib = cuda_build.simple_lib_creator(
self._generate_header_source(),
self._components['LIB_SRC'],
self._kernel.name,
)[self._components['LIB_NAME']]
self._group = None
for pd in self._dat_dict.items():
if issubclass(type(pd[1][0]), cuda_data.PositionDat):
self._group = pd[1][0].group
break
assert self._group is not None, "No cell to particle map found"
new_decomp_flag = self._group.domain.cell_decompose(
self.shell_cutoff
)
if new_decomp_flag:
self._group.get_cell_to_particle_map().create()
self._key = (self.shell_cutoff,
self._group.domain,
self._group.get_position_dat())
_nd = PairLoopCellByCell._cell_lists
if not self._key in _nd.keys() or new_decomp_flag:
_nd[self._key] = cuda_cell.SubCellOccupancyMatrix(
domain=self._group.domain,
cell_width=self.sub_divide_size,
positions=self._group.get_position_dat(),
)
self.cell_list = _nd[self._key]
self._cell_list_count = 0
self._invocations = 0
# get the offset list
oslist = cell.convert_offset_tuples(
cell.radius_cell_decompose(shell_cutoff, self.cell_list.cell_sizes),
self.cell_list.cell_array,
remove_zero=True
)
self.offset_list = cuda_base.Array(ncomp=len(oslist), dtype=ctypes.c_int)
self.offset_list[:] = oslist[:]
def move_to_neighbour(self, directions_matrix=None, dir_counts=None):
"""
Move particles using the passed matrix where rows correspond to
directions.
"""
if self._move_lib is None:
self._move_lib = \
cuda_build.build_static_libs('cudaMoveLib')
self._move_send_ranks, self._move_recv_ranks = \
ppmd.mpi.cartcomm_get_move_send_recv_ranks(self._ccomm)
self._move_send_ranks = ppmd.host.Array(
initial_value=self._move_send_ranks, dtype=ctypes.c_int32)
self._move_recv_ranks = ppmd.host.Array(
initial_value=self._move_recv_ranks, dtype=ctypes.c_int32)
self._move_recv_counts = ppmd.host.Array(ncomp=26,
dtype=ctypes.c_int32)
self._move_send_counts = ppmd.host.Array(initial_value=dir_counts[:],
dtype=ctypes.c_int32)
ndats = len(self.particle_dats)
ptr_t = ndats * ctypes.c_void_p
byte_t = ndats * ctypes.c_int32
ptrs_a = []
byte_a = []
total_bytes = 0
for dat in self.particle_dats:
dath = getattr(self, dat)
ptrs_a.append(dath.ctypes_data)
be = ctypes.sizeof(dath.dtype) * dath.ncomp
byte_a.append(be)
total_bytes += be
# These are arrays len=ndat, of dat pointers and dat byte counts per
# particle
ptrs = ptr_t(*ptrs_a)
byte = byte_t(*byte_a)
cuda_mpi.cuda_mpi_err_check(self._move_lib['cudaMoveStageOne'](
ctypes.c_int32(self._ccomm.py2f()),
self._move_send_ranks.ctypes_data,
self._move_recv_ranks.ctypes_data,
self._move_send_counts.ctypes_data,
self._move_recv_counts.ctypes_data))
total_particles = np.sum(dir_counts[:])
tl = total_particles * total_bytes
if self._move_send_buffer is None:
self._move_send_buffer = cuda_base.Array(ncomp=tl,
dtype=ctypes.c_int8)
elif self._move_send_buffer.ncomp < tl:
self._move_send_buffer.realloc_zeros(tl)
# resize tmp buffers
total_recv_count = np.sum(self._move_recv_counts[:]) * total_bytes
recv_count = np.sum(self._move_recv_counts[:])
if self._move_recv_buffer is None:
self._move_recv_buffer = cuda_base.Array(ncomp=total_recv_count,
dtype=ctypes.c_int8)
elif self._move_recv_buffer.ncomp < total_recv_count:
self._move_recv_buffer.realloc_zeros(total_recv_count)
# resize dats
new_ncomp = self.get_position_dat().npart_local + recv_count
if self._empty_per_particle_flag is None:
self._empty_per_particle_flag = cuda_base.Array(
ncomp=new_ncomp, dtype=ctypes.c_int32)
elif self._empty_per_particle_flag.ncomp < new_ncomp:
self._empty_per_particle_flag.realloc_zeros(new_ncomp)
else:
self._empty_per_particle_flag.zero()
self._resize_callback(self.npart_local + recv_count)
# pack -> S/R unpack
#print ppmd.mpi.MPI_HANDLE.rank, self.domain.boundary[:]
#print self.npart_local, total_particles, recv_count
cuda_mpi.cuda_mpi_err_check(self._move_lib['cudaMoveStageTwo'](
ctypes.c_int32(self._ccomm.py2f()),
ctypes.c_int32(self.npart_local), ctypes.c_int32(total_bytes),
ctypes.c_int32(ndats), self._move_send_counts.ctypes_data,
self._move_recv_counts.ctypes_data,
self._move_send_ranks.ctypes_data,
self._move_recv_ranks.ctypes_data, directions_matrix.ctypes_data,
ctypes.c_int32(directions_matrix.ncol),
self._move_send_buffer.ctypes_data,
self._move_recv_buffer.ctypes_data, ctypes.byref(ptrs),
ctypes.byref(byte), self._empty_per_particle_flag.ctypes_data))
self.npart_local = self.npart_local + recv_count
def __init__(self):
self._domain = None
self._cell_to_particle_map = cuda_cell.CellOccupancyMatrix()
self._halo_manager = None
self._halo_device_version = -1
self._halo_sizes = None
self._halo_cell_max_b = 0
self._halo_cell_max_h = 0
self._halo_h_scan = cuda_base.Array(ncomp=1, dtype=ctypes.c_int32)
self._halo_b_scan = cuda_base.Array(ncomp=1, dtype=ctypes.c_int32)
self._halo_h_groups_se_indices = cuda_base.Array(ncomp=1,
dtype=ctypes.c_int32)
self._halo_b_groups_se_indices = cuda_base.Array(ncomp=1,
dtype=ctypes.c_int32)
self._halo_h_cell_indices = cuda_base.Array(ncomp=1,
dtype=ctypes.c_int32)
self._halo_b_cell_indices = cuda_base.Array(ncomp=1,
dtype=ctypes.c_int32)
self._halo_h_cell_counts = cuda_base.Array(ncomp=1,
dtype=ctypes.c_int32)
self._halo_b_cell_counts = cuda_base.Array(ncomp=1,
dtype=ctypes.c_int32)
self._halo_send_counts = ppmd.host.Array(ncomp=6, dtype=ctypes.c_int32)
self._halo_tmp_space = cuda_base.Array(ncomp=10, dtype=ctypes.c_double)
self._halo_position_shifts = cuda_base.Array(ncomp=18,
dtype=ctypes.c_double)
self._position_dat = None
# Registered particle dats.
self.particle_dats = []
# Local number of particles
self._npart_local = 0
# Global number of particles
self._npart = 0
# do the ParticleDats have gaps in them?
self.compressed = True
""" Bool to determine if the held :class:`~cuda_data.ParticleDat` members have gaps in them. """
self.uncompressed_n = False
# compression vars
self._filter_method = None
self._comp_replacement_find_method = _FindCompressionIndices()
self._compression_lib = None
# State version id
self.version_id = 0
# move vars
self._move_send_ranks = None
self._move_recv_ranks = None
self._move_send_buffer = None
self._move_recv_buffer = None
self._move_lib = None
self._move_send_counts = None
self._move_recv_counts = None
self._empty_per_particle_flag = None
# move vars.
"""If true, all cell lists/ neighbour lists should be rebuilt."""
self.determine_update_funcs = []
self.pre_update_funcs = []
self.post_update_funcs = []
self._gdm = None
self._state_modifier_context = StateModifierContext(self)
self.modifier = StateModifier(self)
