def find_tail_bias(fun_ibiasn, nch_db, vtail, vgs_min, vgs_max, seg_tail_min,
itarg):
seg_tail_iter = BinaryIterator(seg_tail_min, None, step=2)
while seg_tail_iter.has_next():
seg_tail = seg_tail_iter.get_next()
def fun_zero(vgs):
narg = nch_db.get_fun_arg(vgs=vgs, vds=vtail, vbs=0)
return fun_ibiasn(narg) * seg_tail - itarg
if fun_zero(vgs_min) > 0:
# smallest possible current > itarg
seg_tail_iter.down()
if fun_zero(vgs_max) < 0:
# largest possible current < itarg
seg_tail_iter.up()
else:
vbias = sciopt.brentq(fun_zero, vgs_min, vgs_max) # type: float
seg_tail_iter.save_info(vbias)
seg_tail_iter.down()
seg_tail = seg_tail_iter.get_last_save()
vbias = seg_tail_iter.get_last_save_info()
return seg_tail, vbias
async def _upsize_gate_for_del_spec(
self,
dut_params: Dict[str, Any],
tspec: float,
seg_cur: int,
is_nand: bool,
tbm: CombLogicTimingTB,
seg_even: bool,
spec_type: str,
seg_max: Optional[int] = None,
) -> Tuple[int, np.ndarray, np.ndarray]:
if spec_type != 'delay' and spec_type != 'slope':
raise ValueError("spec_type must be either 'delay' or 'slope'.")
bin_iter = BinaryIterator(seg_cur, seg_max, step=1 << seg_even)
while bin_iter.has_next():
new_seg = bin_iter.get_next()
dut_params['params'][
'seg_nand' if is_nand else 'seg_nor'] = new_seg
dut = await self.async_new_dut('nand_nor_upsize', STDCellWrapper,
dut_params)
sim_results = await self.async_simulate_tbm_obj(
'nand_nor_upsize_sim', dut, tbm, self._tb_params)
if spec_type == 'slope':
ans = CombLogicTimingTB.get_output_trf(
sim_results.data, tbm.specs,
'nand_pu' if is_nand else 'nor_pd')
gate_tr, gate_tf = ans
else:
ans = CombLogicTimingTB.get_output_delay(
sim_results.data,
tbm.specs,
'in',
'nand_pu' if is_nand else 'nor_pd',
out_invert=True)
gate_tf, gate_tr = ans
trf_metric = gate_tf if is_nand else gate_tr
if np.max(trf_metric) > tspec:
bin_iter.up(np.max(trf_metric) - tspec)
else:
bin_iter.down(np.max(trf_metric) - tspec)
bin_iter.save_info((new_seg, gate_tr, gate_tf))
info = bin_iter.get_last_save_info()
if info is None:
gate_str = "nand" if is_nand else "nor"
err_str = f'Could not find a size for {gate_str} to meet the target spec of {tspec}.'
self.error(err_str)
seg, tr, tf = info
return seg, tr, tf
def design_tail(specs, itarg, seg_min):
"""Find smallest tail transistor that biases the differential amplifier."""
db = specs['in_db']
sim_env = specs['sim_env']
vds = specs['vdst_min']
in_type = specs['in_type']
if in_type == 'pch':
vds *= -1
ib_fun = db.get_function('ibias', env=sim_env)
vgs_idx = db.get_fun_arg_index('vgs')
vgs_min, vgs_max = ib_fun.get_input_range(vgs_idx)
# binary search on number of fingers.
seg_tail_iter = BinaryIterator(seg_min, None, step=2)
while seg_tail_iter.has_next():
seg_tail = seg_tail_iter.get_next()
def fun_zero(vgs):
farg = db.get_fun_arg(vgs=vgs, vds=vds, vbs=0)
return ib_fun(farg) * seg_tail - itarg
val_min = fun_zero(vgs_min)
val_max = fun_zero(vgs_max)
if val_min > 0 and val_max > 0:
# smallest possible current > itarg
seg_tail_iter.down()
elif val_min < 0 and val_max < 0:
# largest possbile current < itarg
seg_tail_iter.up()
else:
vbias = sciopt.brentq(fun_zero, vgs_min, vgs_max) # type: float
seg_tail_iter.save_info(vbias)
seg_tail_iter.down()
seg_tail = seg_tail_iter.get_last_save()
if seg_tail is None:
raise ValueError('No solution for tail.')
vgs_opt = seg_tail_iter.get_last_save_info()
tail_op = db.query(vbs=0, vds=vds, vgs=vgs_opt)
return seg_tail, tail_op
def fill_symmetric_min_density_info(area,
targ_area,
n_min,
n_max,
sp_min,
sp_max=None,
fill_on_edge=True,
cyclic=False):
# type: (int, int, int, int, int, Optional[int], bool, bool) -> Tuple[Tuple[Any, ...], bool]
"""Fill the given 1-D area as little as possible.
Compute fill location such that the given area is filled with the following properties:
1. the area is as uniform as possible.
2. the area is symmetric with respect to the center
3. all fill blocks have lengths between n_min and n_max.
4. all fill blocks are at least sp_min apart.
Parameters
----------
area : int
total number of space we need to fill.
targ_area : int
target minimum fill area. If not achievable, will do the best that we can.
n_min : int
minimum length of the fill block. Must be less than or equal to n_max.
n_max : int
maximum length of the fill block.
sp_min : int
minimum space between each fill block.
sp_max : Optional[int]
if given, make sure space between blocks does not exceed this value.
Must be greater than sp_min
fill_on_edge : bool
If True, we put fill blocks on area boundary. Otherwise, we put space block on
area boundary.
cyclic : bool
If True, we assume we're filling in a cyclic area (it wraps around).
Returns
-------
info : Tuple[Any, ...]
the fill information tuple.
invert : bool
True if space/fill is inverted.
"""
# first, fill as much as possible
max_result = fill_symmetric_max_density_info(area,
targ_area,
n_min,
n_max,
sp_min,
sp_max=sp_max,
fill_on_edge=fill_on_edge,
cyclic=cyclic)
fill_area, nfill_opt = max_result[0][:2]
if fill_area <= targ_area:
# we cannot/barely meet area spec; return max result
return max_result
# now, reduce fill by doing binary search on n_max
n_max_iter = BinaryIterator(n_min, n_max)
while n_max_iter.has_next():
n_max_cur = n_max_iter.get_next()
try:
info, invert = fill_symmetric_max_num_info(
area,
nfill_opt,
n_min,
n_max_cur,
sp_min,
fill_on_edge=fill_on_edge,
cyclic=cyclic)
fill_area_cur = area - info[0] if invert else info[0]
if invert:
_, sp_cur = _get_min_max_blk_len(info)
else:
sp_cur = sp_min if info[1][2] == 0 else sp_min + 1
if fill_area_cur >= targ_area and (sp_max is None
or sp_cur <= sp_max):
# both specs passed
n_max_iter.save_info((info, invert))
n_max_iter.down()
else:
# reduce n_max too much
n_max_iter.up()
except ValueError:
# get here if n_min == n_max and there's no solution.
n_max_iter.up()
last_save = n_max_iter.get_last_save_info()
if last_save is None:
# no solution, return max result
return max_result
# return new minimum solution
info, invert = last_save
fill_area = area - info[0] if invert else info[0]
return (fill_area, nfill_opt, info[1]), invert
def fill_symmetric_min_density_info(area: int,
n_min: int,
n_max: int,
sp_min: int,
area_specs: List[Tuple[int, int, int]],
sp_max: Optional[int] = None,
fill_on_edge: bool = True,
cyclic: bool = False) -> FillInfo:
"""Fill the given 1-D area to satisfy minimum density constraint
Compute fill location such that the given area is filled with the following properties:
1. the area is as uniform as possible.
2. the area is symmetric with respect to the center
3. all fill blocks have lengths between n_min and n_max.
4. all fill blocks are at least sp_min apart.
Parameters
----------
area : int
total number of space we need to fill.
n_min : int
minimum length of the fill block. Must be less than or equal to n_max.
n_max : int
maximum length of the fill block.
sp_min : int
minimum space between each fill block.
area_specs : List[Tuple[int, int, int]]
list of area specifications, in (target, scale, extension) format.
sp_max : Optional[int]
if given, make sure space between blocks does not exceed this value.
Must be greater than sp_min
fill_on_edge : bool
If True, we put fill blocks on area boundary. Otherwise, we put space block on
area boundary.
cyclic : bool
If True, we assume we're filling in a cyclic area (it wraps around).
Returns
-------
info : FillInfo
the fill information object.
"""
# first, fill as much as possible using scale/extension of the first area spec.
max_result = fill_symmetric_max_density_info(area,
n_min,
n_max,
sp_min,
area_specs,
sp_max=sp_max,
fill_on_edge=fill_on_edge,
cyclic=cyclic)
if not max_result.meet_area_specs(area_specs):
# we cannot meet area spec; return max result
return max_result
# now, reduce fill by doing binary search on n_max
nfill_opt = max_result.num_fill
n_max_iter = BinaryIterator(n_min, n_max)
while n_max_iter.has_next():
n_max_cur = n_max_iter.get_next()
try:
info = fill_symmetric_max_num_info(area,
nfill_opt,
n_min,
n_max_cur,
sp_min,
fill_on_edge=fill_on_edge,
cyclic=cyclic)
if info.meet_area_specs(area_specs) and (sp_max is None
or info.sp_max <= sp_max):
# both specs passed
n_max_iter.save_info(info)
n_max_iter.down()
else:
# reduce n_max too much
n_max_iter.up()
except ValueError:
# get here if n_min == n_max and there's no solution.
n_max_iter.up()
last_save = n_max_iter.get_last_save_info()
if last_save is None:
# no solution, return max result
return max_result
else:
max_result = last_save
# see if we can further reduce fill by doing binary search on nfill_opt
nfill_iter = BinaryIterator(1, nfill_opt)
n_max = n_max_iter.get_last_save()
while nfill_iter.has_next():
nfill_cur = nfill_iter.get_next()
try:
info = fill_symmetric_max_num_info(area,
nfill_cur,
n_min,
n_max,
sp_min,
fill_on_edge=fill_on_edge,
cyclic=cyclic)
if info.meet_area_specs(area_specs) and (sp_max is None
or info.sp_max <= sp_max):
# both specs passed
nfill_iter.save_info(info)
nfill_iter.down()
else:
# reduce nfill too much
nfill_iter.up()
except ValueError:
nfill_iter.up()
last_save = nfill_iter.get_last_save_info()
if last_save is None:
return max_result
# return new minimum solution
return last_save
async def async_design(self, pinfo: Mapping[str, Any], nbits: int,
rtol: float, atol: float, tbit: float, trf: float,
cload: float, mc_params: Param, num_cores: int,
target: Mapping[str, Any],
delay_cell_params: Mapping[str, Any],
**kwargs: Mapping[str, Any]) -> Mapping[str, Any]:
td_min = target['td_min']
td_max = target['td_max']
t_max = target['t_max']
td_sigma = target['td_sigma']
tristate_seg = kwargs.get('tristate_seg', self.global_info['seg_min'])
tristate_stack = kwargs.get('tristate_stack', 1)
seg_buf_abs_max = kwargs.get('seg_buf_abs_max', 50)
seg_buf_max_override = kwargs.get('seg_buf_max_override', None)
seg_buf_min_override = kwargs.get('seg_buf_min_override', None)
design_using_signoff = kwargs.get('design_using_signoff', False)
mc_corner = kwargs.get('mc_corner', 'tt_25')
mc_env_override = kwargs.get("mc_env_override", None)
mc_worst_corner = kwargs.get("mc_worst_corner", True)
plot_result: bool = kwargs.get('plot_result', False)
dsn_monte_carlo: bool = kwargs.get('dsn_monte_carlo', True)
gen_specs: Optional[Mapping[str,
Any]] = kwargs.get('gen_cell_specs', None)
gen_cell_args: Optional[Mapping[str, Any]] = kwargs.get(
'gen_cell_args', None)
# 0. Setup design environments and the testbench manager
if design_using_signoff:
dsn_envs = self.global_info['signoff_envs']
dsn_env_names = dsn_envs['all_corners']['envs']
dsn_env_vdds = dsn_envs['all_corners']['vdd']
else:
dsn_envs = self.global_info['dsn_envs']
dsn_env_names = [
env for dct in dsn_envs.values() for env in dct['env']
]
dsn_env_vdds = {
e: dsn_envs[c]['vdd']
for c in dsn_envs.keys() for e in dsn_envs[c]['env']
}
if not mc_worst_corner and not mc_env_override:
raise ValueError(
"If not performing mc on the worst corner, specify mc_env_override!"
)
dut_pins = [
'a_in', 'b_in', 'intout', 'VDD', 'VSS', f'sp<{nbits - 1}:0>',
f'sn<{nbits - 1}:0>', 'a_in_buf'
]
tbm_dict = {}
for dsn_env in dsn_env_names:
tbm_specs = self._get_tbm_specs(
[dsn_env], dict(vdd={dsn_env: dsn_env_vdds[dsn_env]}),
dut_pins, tbit, trf, cload, nbits, rtol, atol)
tbm = cast(DigitalTranTB, self.make_tbm(DigitalTranTB, tbm_specs))
tbm_dict[dsn_env] = tbm
tbm_params = dict()
# 1. Setup the base phase interpolator and extract the input cap
pwr_domains = dict(b_in=('VSS', 'VDD'),
a_in=('VSS', 'VDD'),
out=('VSS', 'VDD'))
cin_dut_conns = dict(a_in=1)
for i in range(nbits):
for name, value in zip(['a_en', 'b_en', 'a_enb', 'b_enb'],
[1, 0, 0, 1]):
cin_dut_conns[f'{name}<{i}>'] = value
pwr_domains[f'{name}<{i}>'] = ('VSS', 'VDD')
gen_params = dict(cls_name=PhaseInterpolator.get_qualified_name(),
params=dict(
pinfo=pinfo,
unit_params={
'seg': tristate_seg,
'stack_p': tristate_stack,
'stack_n': tristate_stack
},
inv_params={
'seg': 2,
'stack_p': 1,
'stack_n': 1
},
nbits=nbits,
draw_sub=True,
export_outb=True,
abut_tristates=True,
))
pi_in_cap = await self._get_input_cap(
gen_params,
'b_in',
cload,
cin_dut_conns,
pwr_domains, [dict(pin='out', type='cap', value='c_out')],
vdd=dsn_env_vdds['tt_25'],
sim_envs=['tt_25'])
# 2. Setup the base delay cell and extract it's input cap
pin_names = ['bk1', 'ci_p', 'co_p', 'in_p', 'out_p']
pwr_domains = {pin_name: ('VSS', 'VDD') for pin_name in pin_names}
cin_dut_conns = dict(bk1=1, ci_p=0)
load_list = [
dict(pin='out_p', type='cap', value='c_out'),
dict(pin='co_p', type='cap', value='c_out')
]
gen_params = dict(cls_name=DelayCellCore.get_qualified_name(),
params=dict(pinfo=pinfo,
stand_alone=True,
**delay_cell_params))
dc_in_cap = await self._get_input_cap(gen_params,
'ci_p',
cload,
cin_dut_conns,
pwr_domains,
load_list,
vdd=dsn_env_vdds['tt_25'],
sim_envs=['tt_25'])
# 3. Size the delay cell to be able to drive the phase interpolator
dc_up_scale_factor = int(round(pi_in_cap / dc_in_cap))
delay_cell_params['seg_dict']['in'] *= dc_up_scale_factor
delay_cell_params['seg_dict']['out'] *= dc_up_scale_factor
delay_cell_params['seg_dict']['sr'] *= dc_up_scale_factor
nand_seg = delay_cell_params['seg_dict']['out'] * 2
inv_in_cap = self.global_info['cin_inv']['cin_per_seg']
inv_seg = int(round(np.sqrt(dc_in_cap * pi_in_cap) / inv_in_cap))
# 4. Upsize the buffer inverter on the output
self.log('-' * 80)
if seg_buf_min_override:
self.log(f"Minimum Segments Overridden to {seg_buf_min_override}")
min_seg_buf = seg_buf_min_override
else:
self.log('Find the min size for all the codes to be positive')
seg_buf_min_iter = BinaryIterator(2, None, 2)
while seg_buf_min_iter.has_next():
_seg_buf = seg_buf_min_iter.get_next()
dut_params = self._update_dut_params(
pinfo,
nbits,
tristate_seg,
seg_buf=_seg_buf,
seg_inv=inv_seg,
seg_nand=nand_seg,
num_cores=num_cores,
dc_params=delay_cell_params)
results = await self._measure_times(dsn_env_names,
tbm_dict,
dut_params,
tbm_params,
tbit,
nbits,
name=f'sim_min_{_seg_buf}')
# find min and max delay step
tstep_min = results['min_step']
tstep_max = results['max_step']
self.log(
f"Got min delay {tstep_min}, max delay {tstep_max}, with "
f"{_seg_buf} segments")
if tstep_min < 0:
seg_buf_min_iter.up()
else:
seg_buf_min_iter.save()
seg_buf_min_iter.down()
min_seg_buf = seg_buf_min_iter.get_last_save()
self.log('-' * 80)
if seg_buf_max_override:
self.log(f'Maximum Segments Overridden to {seg_buf_max_override}')
max_seg_buf = seg_buf_max_override
else:
self.log(
'Now find the maximum size for all the codes to be positive')
seg_buf_max_iter = BinaryIterator(10, None, 2)
max_reached = False
while seg_buf_max_iter.has_next():
_seg_buf = seg_buf_max_iter.get_next()
dut_params = self._update_dut_params(
pinfo,
nbits,
tristate_seg,
seg_buf=_seg_buf,
seg_inv=inv_seg,
seg_nand=nand_seg,
num_cores=num_cores,
dc_params=delay_cell_params)
results = await self._measure_times(dsn_env_names,
tbm_dict,
dut_params,
tbm_params,
tbit,
nbits,
name=f'sim_max_{_seg_buf}')
# find min and max delay step
tstep_min = results['min_step']
tstep_max = results['max_step']
self.log(
f"Got min delay {tstep_min}, max delay {tstep_max}, with "
f"{_seg_buf} segments")
if tstep_min < 0:
seg_buf_max_iter.down()
elif _seg_buf > seg_buf_abs_max:
max_reached = True
break
else:
seg_buf_max_iter.save()
seg_buf_max_iter.up()
max_seg_buf = seg_buf_max_iter.get_last_save(
) if not max_reached else seg_buf_abs_max
self.log('-' * 80)
self.log(
f'Minimum Buffer segments to keep positive delays: {min_seg_buf}')
self.log(
f'Maximum Buffer segments to keep positive delays: {max_seg_buf}')
seg_buf_bin_iter = BinaryIterator(min_seg_buf, max_seg_buf, 2)
while seg_buf_bin_iter.has_next():
_seg_buf = seg_buf_bin_iter.get_next()
dut_params = self._update_dut_params(pinfo,
nbits,
tristate_seg,
seg_buf=_seg_buf,
seg_inv=inv_seg,
seg_nand=nand_seg,
num_cores=num_cores,
dc_params=delay_cell_params)
results = await self._measure_times(dsn_env_names, tbm_dict,
dut_params, tbm_params, tbit,
nbits, 'sim_size')
tdelay_max = results['max_dly']
tstep_min = results['min_step']
tstep_max = results['max_step']
if tdelay_max > t_max and tstep_min > td_min and tstep_max < td_max:
# delay constraint violated, linearity constraint met
seg_buf_bin_iter.down()
elif tdelay_max < t_max and (tstep_min < td_min
or tstep_max > td_max):
# delay constraint met, linearity constraint violated
seg_buf_bin_iter.up()
elif tdelay_max < t_max and tstep_min > td_min and tstep_max < td_max:
# both constraints met
seg_buf_bin_iter.save_info((dut_params, results))
seg_buf_bin_iter.down()
else:
self.error(
'Both delay and linearity constraints violated, please relax specs.'
)
seg_buf_final = seg_buf_bin_iter.get_last_save()
if not seg_buf_final:
self.error(
"Design failed!, unable to meet linearity specs within range of inv sizes"
)
self.log(
f'Final output buffer size is {seg_buf_final}, before Monte Carlo sim.'
)
dut_params, results = seg_buf_bin_iter.get_last_save_info()
if dsn_monte_carlo:
# 5. Monte Carlo simulations
mc_tbm_dict = {}
if mc_worst_corner:
mc_envs = [mc_corner]
mc_vdd = dict(vdd={mc_corner: dsn_env_vdds[mc_corner]})
mc_tbm_specs = self._get_tbm_specs([mc_corner], mc_vdd,
dut_pins, tbit, trf, cload,
nbits, rtol, atol)
mc_tbm_specs['monte_carlo_params'] = mc_params
mc_tbm = cast(DigitalTranTB,
self.make_tbm(DigitalTranTB, mc_tbm_specs))
mc_tbm_dict[mc_corner] = mc_tbm
else:
# TODO
mc_envs = ...
...
dut_params = self._update_dut_params(pinfo,
nbits,
tristate_seg,
seg_buf=seg_buf_final,
seg_inv=inv_seg,
seg_nand=nand_seg,
num_cores=num_cores,
dc_params=delay_cell_params)
mc_results = await self._measure_times(mc_envs,
mc_tbm_dict,
dut_params,
tbm_params,
tbit,
nbits,
name='sim_mc_pre')
mc_factor, sigma_max = self._get_mc_factor(mc_results, td_sigma)
self.log(f'Max std. dev. is {sigma_max}')
self.log(f'Upscale everything by {mc_factor}')
self.log('-' * 80)
# 6. Final verification
seg_unit_final = int(np.ceil(tristate_seg * mc_factor))
seg_unit_final += seg_unit_final & 1 # layout constraint
seg_buf_final = int(np.ceil(seg_buf_final * mc_factor))
seg_buf_final += seg_buf_final & 1 # layout constraint
delay_cell_params_scale = copy.deepcopy(delay_cell_params)
for key in delay_cell_params['seg_dict']:
delay_cell_params_scale['seg_dict'][key] = int(
np.ceil(delay_cell_params['seg_dict'][key] * mc_factor))
nand_seg = int(np.ceil(nand_seg * mc_factor))
inv_seg = int(np.ceil(inv_seg * mc_factor))
dut_params = self._update_dut_params(
pinfo,
nbits,
seg_unit_final,
seg_buf=seg_buf_final,
seg_inv=inv_seg,
seg_nand=nand_seg,
num_cores=num_cores,
dc_params=delay_cell_params_scale)
results = await self._measure_times(dsn_env_names,
tbm_dict,
dut_params,
tbm_params,
tbit,
nbits,
name='sim_sized')
mc_results = await self._measure_times(mc_envs,
mc_tbm_dict,
dut_params,
tbm_params,
tbit,
nbits,
name='sim_mc_post')
_, sigma_max = self._get_mc_factor(mc_results, td_sigma)
self.log(f'Final Sigma: {sigma_max}')
self.log('-' * 80)
else:
seg_unit_final = tristate_seg
delay_cell_params_scale = delay_cell_params
self.log('-' * 80)
self.log(f'dsn_envs: {dsn_env_names}')
self.log(f'final results:\n{pprint.pformat(results, width=100)}')
if plot_result:
from matplotlib import pyplot as plt
plt.figure(1)
ax: Any = plt.subplot(2, 1, 1)
xvec = np.arange(0, results['tdr_step'].shape[1])
for idx, sim_env in enumerate(dsn_env_names):
tdr = results['tdrs'][idx, :-1].flatten()
plt.step(xvec, tdr, where='mid', label=sim_env)
ax.legend()
ax.set_ylabel('Rise Delay (s)')
ax = plt.subplot(2, 1, 2)
for idx, sim_env in enumerate(dsn_env_names):
tdr_step = results['tdr_step'][idx, :].flatten()
ax.scatter(xvec, tdr_step, label=sim_env)
ax.set_ylim(ymin=td_min, ymax=td_max)
ax.legend()
ax.set_ylabel('Rise Delay Step (s)')
ax.set_xlabel('Code')
plt.show()
if gen_specs is not None and gen_cell_args is not None:
gen_cell_specs = dict(
lay_class=IPMarginTemplate.get_qualified_name(),
params=dict(
cls_name=GenericWrapper.get_qualified_name(),
params=dict(
cls_name=PhaseInterpolatorWithDelay.get_qualified_name(
),
params=dut_params,
),
),
**gen_specs,
)
return dict(gen_specs=gen_cell_specs, gen_args=gen_cell_args)
return dict(
seg_unit=seg_unit_final,
seg_buf=seg_buf_final,
seg_dc=delay_cell_params_scale['seg_dict'],
nand_seg=nand_seg,
inv_seg=inv_seg,
)
async def _get_stack(
self,
dut_params: Dict[str, Any],
mm_specs: Dict[str, Any],
r_targ: float,
stack_max: Optional[int] = None) -> Tuple[np.ndarray, np.ndarray]:
"""Binary searches the stack size to hit target r_targ output resistance.
If stack_max is None, we skip sizing. This is set when sizing the main driver.
NOTE: this function modifies dut_params and tbm_specs.
Parameters
----------
dut_params: Dict[str, Any]
Driver generator parameters
mm_specs: Dict[str, Any]
Specs for DriverPullUpDownMM
r_targ:
Target output resistance
stack_max:
Maximum allowed transistor stack size
Returns
-------
r_pu, r_pd: Tuple[np.ndarray, np.ndarray]
Measured pull-up / pull-down output resistance across given corners
"""
if not stack_max:
dut_params['stack'] = 1
sim_id = f'stack_1'
r_pu, r_pd = await self._get_resistance(sim_id, dut_params,
mm_specs)
return r_pu, r_pd
r_best = 0.0
bin_iter = BinaryIterator(1, None)
while bin_iter.has_next():
cur_stack = bin_iter.get_next()
while bin_iter.has_next() and cur_stack > stack_max:
bin_iter.down(float('inf'))
cur_stack = bin_iter.get_next()
if cur_stack > stack_max:
break
dut_params['stack'] = cur_stack
sim_id = f'stack_{cur_stack}'
r_pu, r_pd = await self._get_resistance(sim_id, dut_params,
mm_specs)
r_test = min(np.min(r_pu), np.min(r_pd))
r_best = max(r_test, r_best)
if r_targ > min(np.min(r_pu), np.min(r_pd)):
bin_iter.up(r_targ - min(np.min(r_pu), np.min(r_pd)))
else:
bin_iter.save_info((cur_stack, r_pu, r_pd))
bin_iter.down(r_targ - min(np.min(r_pu), np.min(r_pd)))
save_info = bin_iter.get_last_save_info()
if save_info is None:
self.error(f'Cannot meet spec with stack_max = {stack_max}, '
f'r_best = {r_best:.4g}')
stack, r_pu, r_pd = bin_iter.get_last_save_info()
dut_params['stack'] = stack
return r_pu, r_pd
def design_amp(amp_specs, nch_db, pch_db):
sim_env = amp_specs['sim_env']
vdd = amp_specs['vdd']
vtail = amp_specs['vtail']
vgs_res = amp_specs['vgs_res']
gain_min = amp_specs['gain_min']
bw_min = amp_specs['bw_min']
cload = amp_specs['cload']
fun_ibiasn = nch_db.get_function('ibias', env=sim_env)
fun_gmn = nch_db.get_function('gm', env=sim_env)
fun_gdsn = nch_db.get_function('gds', env=sim_env)
fun_cdn = nch_db.get_function('cdb', env=sim_env) + nch_db.get_function(
'cds', env=sim_env)
fun_cgsn = nch_db.get_function('cgs', env=sim_env)
fun_ibiasp = pch_db.get_function('ibias', env=sim_env)
fun_gdsp = pch_db.get_function('gds', env=sim_env)
fun_cdp = pch_db.get_function('cdd', env=sim_env)
vgsn_idx = nch_db.get_fun_arg_index('vgs')
vgsn_min, vgsn_max = fun_ibiasn.get_input_range(vgsn_idx)
num_pts = int(math.ceil((vgsn_max - vgsn_min) / vgs_res))
vgs_list = np.linspace(vgsn_min, vgsn_max, num_pts + 1).tolist()
vgsp_idx = pch_db.get_fun_arg_index('vgs')
vgsp_min, vgsp_max = fun_ibiasp.get_input_range(vgsp_idx)
# sweep vgs, find best point
performance = None
for vgsn_cur in vgs_list:
vout = vgsn_cur + vtail
narg = nch_db.get_fun_arg(vgs=vgsn_cur, vds=vgsn_cur, vbs=vtail)
ibiasn_unit = fun_ibiasn(narg)
gmn_unit = fun_gmn(narg)
gdsn_unit = fun_gdsn(narg)
cdn_unit = fun_cdn(narg)
cgsn_unit = fun_cgsn(narg)
# find max gain
def gain_fun1(vgsp_test):
parg_test = pch_db.get_fun_arg(vgs=vgsp_test,
vds=vout - vdd,
vbs=0)
ibiasp_unit_test = fun_ibiasp(parg_test)
gdsp_unit_test = fun_gdsp(parg_test)
return gmn_unit / ibiasn_unit / (gdsn_unit / ibiasn_unit +
gdsp_unit_test / ibiasp_unit_test)
result = minimize_cost_golden_float(gain_fun1,
gain_min,
vgsp_min,
vgsp_max,
tol=vgs_res / 10)
opt_vgsp = result.x
if opt_vgsp is None:
print('vgsn = %.4g, max gain: %.4g' % (vgsn_cur, result.vmax))
break
# get number of input fingers needed to achieve gain_max with minimum number of load fingers
seg_in_init = fun_ibiasp(
pch_db.get_fun_arg(vgs=opt_vgsp, vds=vout - vdd,
vbs=0)) * 2 / ibiasn_unit
seg_in_init = int(round(seg_in_init / 2)) * 2
# sweep gm size
seg_in_iter = BinaryIterator(2, None, step=2)
seg_in_iter.set_current(seg_in_init)
while seg_in_iter.has_next():
seg_in = seg_in_iter.get_next()
ibiasn = seg_in * ibiasn_unit
gmn = seg_in * gmn_unit
gdsn = seg_in * gdsn_unit
# sweep load size
seg_load_iter = BinaryIterator(2, None, step=2)
while seg_load_iter.has_next():
seg_load = seg_load_iter.get_next()
vbp, sgn = find_load_bias(pch_db, vdd, vout, vgsp_min,
vgsp_max, ibiasn, seg_load,
fun_ibiasp)
if vbp is None:
if sgn > 0:
seg_load_iter.up()
else:
seg_load_iter.down()
else:
parg = pch_db.get_fun_arg(vgs=vbp - vdd,
vds=vout - vdd,
vbs=0)
gdsp = seg_load * fun_gdsp(parg)
if gmn / (gdsp + gdsn) >= gain_min:
seg_load_iter.save_info((vbp, parg))
seg_load_iter.down()
else:
seg_load_iter.up()
seg_load = seg_load_iter.get_last_save()
if seg_load is None:
# no load solution -> cannot meet gain spec.
break
vbp, parg = seg_load_iter.get_last_save_info()
gdsp = seg_load * fun_gdsp(parg)
cdp = seg_load * fun_cdp(parg)
cdn = seg_in * cdn_unit
cgsn = seg_in * cgsn_unit
ro_cur = 1 / (gdsp + gdsn)
gain_cur = gmn * ro_cur
cpar_cur = cdn + cdp + (1 + 1 / gain_cur) * cgsn
# check intrinsic bandwidth good
if 1 / (ro_cur * cpar_cur * 2 * np.pi) < bw_min:
break
cload_cur = cload + cpar_cur
bw_cur = 1 / (ro_cur * cload_cur * 2 * np.pi)
if bw_cur < bw_min:
seg_in_iter.up()
else:
seg_in_iter.save_info(
(seg_load, vbp, ibiasn, gain_cur, bw_cur))
seg_in_iter.down()
if seg_in_iter.get_last_save() is None:
continue
seg_in = seg_in_iter.get_last_save()
seg_load, vbp, ibiasn, gain_cur, bw_cur = seg_in_iter.get_last_save_info(
)
if performance is None or performance[0] > ibiasn:
performance = (ibiasn, gain_cur, bw_cur, seg_in, seg_load,
vgsn_cur, vbp)
if performance is None:
return None
ibias_opt, gain_opt, bw_opt, seg_in, seg_load, vgs_in, vload = performance
vio = vtail + vgs_in
seg_tail, vbias = find_tail_bias(fun_ibiasn, nch_db, vtail, vgsn_min,
vgsn_max, seg_in, ibias_opt)
return dict(
ibias=2 * ibias_opt,
gain=gain_opt,
bw=bw_opt,
seg_in=seg_in,
seg_load=seg_load,
seg_tail=seg_tail,
vtail=vbias,
vindc=vio,
voutdc=vio,
vload=vload,
vgs_in=vgs_in,
)
def draw_layout(self):
# type: () -> None
top_layer = self.params['top_layer']
lch = self.params['lch']
w = self.params['w']
sub_type = self.params['sub_type']
threshold = self.params['threshold']
port_width = self.params['port_width']
well_width = self.params['well_width']
end_mode = self.params['end_mode']
is_passive = self.params['is_passive']
max_nxblk = self.params['max_nxblk']
port_tid = self.params['port_tid']
show_pins = self.params['show_pins']
half_blk_y = self.params['half_blk_y']
half_blk_x = self.params['half_blk_x']
res = self.grid.resolution
well_width = int(round(well_width / res))
right_end = (end_mode & 8) != 0
left_end = (end_mode & 4) != 0
top_end = (end_mode & 2) != 0
bot_end = (end_mode & 1) != 0
# get layout info, also set RoutingGrid to substrate grid.
layout_info = AnalogBaseInfo(self.grid,
lch,
0,
top_layer=top_layer,
end_mode=end_mode,
half_blk_y=half_blk_y,
half_blk_x=half_blk_x)
# compute template width in number of sd pitches
# find maximum number of fingers we can draw
bin_iter = BinaryIterator(1, None)
while bin_iter.has_next():
cur_fg = bin_iter.get_next()
cur_pinfo = layout_info.get_placement_info(cur_fg)
cur_core_width = cur_pinfo.core_width
if cur_core_width == well_width:
bin_iter.save_info(cur_pinfo)
break
elif cur_core_width < well_width:
bin_iter.save_info(cur_pinfo)
bin_iter.up()
else:
bin_iter.down()
sub_fg_tot = bin_iter.get_last_save()
if sub_fg_tot is None:
raise ValueError('Cannot draw substrate that fit in width: %d' %
well_width)
# check width parity requirement
if max_nxblk > 0:
blkw = self.grid.get_block_size(top_layer, unit_mode=True)[0]
place_info = bin_iter.get_last_save_info()
cur_nxblk = place_info.tot_width // blkw
while sub_fg_tot > 0 and (cur_nxblk > max_nxblk or
(max_nxblk - cur_nxblk) % 2 != 0):
sub_fg_tot -= 1
place_info = layout_info.get_placement_info(sub_fg_tot)
cur_nxblk = place_info.tot_width // blkw
if sub_fg_tot <= 0:
raise ValueError('Cannot draw substrate with width = %d, '
'max_nxblk = %d' % (well_width, max_nxblk))
layout_info.set_fg_tot(sub_fg_tot)
self.grid = layout_info.grid
place_info = layout_info.get_placement_info(sub_fg_tot)
edgel_x0 = place_info.edge_margins[0]
tot_width = place_info.tot_width
# create masters
master_list = [
self.new_template(params=dict(
lch=lch,
fg=sub_fg_tot,
sub_type=sub_type,
threshold=threshold,
is_end=bot_end,
top_layer=top_layer,
),
temp_cls=AnalogEndRow),
self.new_template(params=dict(
lch=lch,
w=w,
sub_type=sub_type,
threshold=threshold,
fg=sub_fg_tot,
top_layer=top_layer,
options=dict(is_passive=is_passive),
),
temp_cls=AnalogSubstrate),
self.new_template(params=dict(
lch=lch,
fg=sub_fg_tot,
sub_type=sub_type,
threshold=threshold,
is_end=top_end,
top_layer=top_layer,
),
temp_cls=AnalogEndRow),
]
ycur = 0
array_box = BBox.get_invalid_bbox()
sub_conn, inst = None, None
for master, orient in zip(master_list, ['R0', 'R0', 'MX']):
if orient == 'MX':
ycur += master.array_box.top_unit
name_id = master.get_layout_basename()
edge_layout_info = master.get_edge_layout_info()
xcur = edgel_x0
if left_end:
edge_info = master.get_left_edge_info()
edge_params = dict(
is_end=True,
guard_ring_nf=0,
name_id=name_id,
layout_info=edge_layout_info,
adj_blk_info=edge_info,
)
edge_master = self.new_template(params=edge_params,
temp_cls=AnalogEdge)
if not edge_master.is_empty:
edge_inst = self.add_instance(edge_master,
loc=(edgel_x0, ycur),
orient=orient,
unit_mode=True)
array_box = array_box.merge(edge_inst.array_box)
xcur = edge_inst.array_box.right_unit
inst = self.add_instance(master,
loc=(xcur, ycur),
orient=orient,
unit_mode=True)
array_box = array_box.merge(inst.array_box)
if isinstance(master, AnalogSubstrate):
conn_params = dict(
layout_info=edge_layout_info,
layout_name=name_id + '_subconn',
is_laygo=False,
)
conn_master = self.new_template(params=conn_params,
temp_cls=AnalogSubstrateConn)
sub_conn = self.add_instance(conn_master,
loc=(xcur, ycur),
orient=orient,
unit_mode=True)
xcur = inst.array_box.right_unit
if right_end:
edge_info = master.get_right_edge_info()
edge_params = dict(
is_end=True,
guard_ring_nf=0,
name_id=name_id,
layout_info=edge_layout_info,
adj_blk_info=edge_info,
)
edge_master = self.new_template(params=edge_params,
temp_cls=AnalogEdge)
if not edge_master.is_empty:
xcur += edge_master.array_box.right_unit
eor = 'MY' if orient == 'R0' else 'R180'
edge_inst = self.add_instance(edge_master,
loc=(xcur, ycur),
orient=eor,
unit_mode=True)
array_box = array_box.merge(edge_inst.array_box)
if orient == 'R0':
ycur += master.array_box.top_unit
# calculate substrate Y coordinates
imp_yb, thres_yb = master_list[0].sub_ysep
imp_yt, thres_yt = master_list[2].sub_ysep
self._sub_bndy = (imp_yb, ycur - imp_yt), (thres_yb, ycur - thres_yt)
# get left/right substrate coordinates
tot_imp_box = BBox.get_invalid_bbox()
for lay in self.grid.tech_info.get_implant_layers('ptap'):
tot_imp_box = tot_imp_box.merge(self.get_rect_bbox(lay))
for lay in self.grid.tech_info.get_implant_layers('ntap'):
tot_imp_box = tot_imp_box.merge(self.get_rect_bbox(lay))
if not tot_imp_box.is_physical():
self._sub_bndx = None, None
else:
self._sub_bndx = tot_imp_box.left_unit, tot_imp_box.right_unit
# set array box and size
self.array_box = array_box
bound_box = BBox(0,
0,
tot_width,
inst.bound_box.top_unit,
res,
unit_mode=True)
if self.grid.size_defined(top_layer):
self.set_size_from_bound_box(top_layer, bound_box)
else:
self.prim_bound_box = bound_box
self.prim_top_layer = top_layer
hm_layer = layout_info.mconn_port_layer + 1
if port_tid is None:
# find center track index
hm_mid = self.grid.coord_to_nearest_track(hm_layer,
self.array_box.yc_unit,
mode=0,
half_track=True,
unit_mode=True)
# connect to horizontal metal layer.
hm_pitch = self.grid.get_track_pitch(hm_layer, unit_mode=True)
ntr = self.array_box.height_unit // hm_pitch # type: int
if port_width is None:
port_width = self.grid.get_max_track_width(
hm_layer, 1, ntr, half_end_space=False)
port_tid = TrackID(hm_layer, hm_mid, width=port_width)
else:
port_tid = TrackID(hm_layer, port_tid[0], width=port_tid[1])
port_name = 'VDD' if sub_type == 'ntap' else 'VSS'
sub_wires = self.connect_to_tracks(
sub_conn.get_port(port_name).get_pins(hm_layer - 1), port_tid)
self.add_pin(port_name, sub_wires, show=show_pins)
self._fg_tot = sub_fg_tot
async def _design_output_inverter(self, inv_in_pseg: int, inv_in_nseg: int,
pseg: int, nseg: int, inv_nseg: int,
inv_pseg: int, out_inv_m: int,
fanout: float, pinfo: Any,
tbm_specs: Dict[str, Any], has_rst, vin,
vout) -> int:
"""
Given all other sizes and total output inverter segments, this function will optimize the output inverter
to minimize rise/fall mismatch.
"""
tb_params = self._get_full_tb_params()
# Use a binary iterator to find the PMOS size
iterator = BinaryIterator(-out_inv_m + 1, out_inv_m - 1)
err_best = float('inf')
all_corners = get_tech_global_info(
'bag3_digital')['signoff_envs']['all_corners']
while iterator.has_next():
pseg_off = iterator.get_next()
dut_params = self._get_lvl_shift_params_dict(pinfo,
pseg,
nseg,
inv_pseg,
inv_nseg,
inv_in_nseg,
inv_in_pseg,
out_inv_m,
has_rst,
dual_output=False,
skew_out=True,
out_pseg_off=pseg_off)
dut = await self.async_new_dut('lvshift', STDCellWrapper,
dut_params)
err_worst = -1 * float('Inf')
worst_env = ''
sim_worst = None
for env in all_corners['envs']:
tbm_specs['sim_envs'] = [env]
tbm_specs['sim_params']['vdd_in'] = all_corners[vin][env]
tbm_specs['sim_params']['vdd'] = all_corners[vout][env]
tbm = cast(CombLogicTimingTB,
self.make_tbm(CombLogicTimingTB, tbm_specs))
sim_results = await self.async_simulate_tbm_obj(
f'sim_output_inv_pseg_{pseg_off}_{env}', dut, tbm,
tb_params)
tdr_cur, tdf_cur = CombLogicTimingTB.get_output_delay(
sim_results.data,
tbm.specs,
'in',
'out',
False,
in_pwr='vdd_in',
out_pwr='vdd')
if math.isinf(np.max(tdr_cur)) or math.isinf(np.max(tdf_cur)):
raise ValueError("Got infinite delay!")
if tdr_cur[0] < 0 or tdf_cur[0] < 0:
raise ValueError("Got negative delay.")
err_cur = np.abs(tdr_cur[0] - tdf_cur[0])
if err_cur > err_worst:
err_worst = err_cur
worst_env = env
tdr = tdr_cur[0]
tdf = tdf_cur[0]
sim_worst = sim_results
'''
print(f'iter: {pseg_off}')
print(f'env: {worst_env}, tdr: {tdr}, tdf: {tdf}')
breakpoint()
'''
if tdr < tdf:
iterator.down(tdr - tdf)
else:
iterator.up(tdr - tdf)
err_abs = np.abs(tdr - tdf)
if err_abs < err_best:
err_best = err_abs
iterator.save_info(pseg_off)
pseg_off = iterator.get_last_save_info()
if pseg_off is None:
raise ValueError("Could not find PMOS size to match target delay")
self.log(f'Calculated output inverter to skew PMOS by {pseg_off}.')
return pseg_off
async def _design_lvl_shift_inv_pun(self, pseg: int, nseg: int,
inv_nseg: int, out_inv_m: int,
fanout: float, pinfo: Any,
tbm_specs: Dict[str, Any], has_rst,
dual_output, vin,
vout) -> Tuple[int, int]:
"""
Given the NMOS pull down size, this function will design the PMOS pull up so that the delay
mismatch is minimized.
# TODO: Need to double check on how this handles corners
"""
inv_beta = get_tech_global_info('bag3_digital')['inv_beta']
tb_params = self._get_full_tb_params()
# Use a binary iterator to find the PMOS size
load_seg = nseg + (pseg if has_rst else 0)
inv_pseg_nom = int(
np.round(inv_beta * load_seg / ((1 + inv_beta) * fanout)))
inv_pseg_nom = 1 if inv_pseg_nom == 0 else inv_pseg_nom
iterator = BinaryIterator(-inv_pseg_nom + 1, 0)
err_best = float('inf')
inv_in_nseg, inv_in_pseg = self._size_input_inv_for_fanout(
inv_pseg_nom, inv_nseg, pseg, nseg, fanout, has_rst)
all_corners = get_tech_global_info(
'bag3_digital')['signoff_envs']['all_corners']
while iterator.has_next():
pseg_off = iterator.get_next()
inv_pseg = inv_pseg_nom + pseg_off
dut_params = self._get_lvl_shift_params_dict(
pinfo, pseg, nseg, inv_pseg, inv_nseg, inv_in_nseg,
inv_in_pseg, out_inv_m, has_rst, dual_output)
dut = await self.async_new_dut('lvshift', STDCellWrapper,
dut_params)
err_worst = -1 * float('Inf')
for env in all_corners['envs']:
tbm_specs['sim_envs'] = [env]
tbm_specs['sim_params']['vdd_in'] = all_corners[vin][env]
tbm_specs['sim_params']['vdd'] = all_corners[vout][env]
tbm = cast(CombLogicTimingTB,
self.make_tbm(CombLogicTimingTB, tbm_specs))
sim_results = await self.async_simulate_tbm_obj(
f'sim_inv_pseg_{inv_pseg}_{env}', dut, tbm, tb_params)
tdr_cur, tdf_cur = CombLogicTimingTB.get_output_delay(
sim_results.data,
tbm.specs,
'in',
'out',
False,
in_pwr='vdd_in',
out_pwr='vdd')
'''
plt.figure()
plt.plot(sim_results.data['time'].flatten(), sim_results.data['in'].flatten(), 'b')
plt.plot(sim_results.data['time'].flatten(), sim_results.data['inb_buf'].flatten(), 'g')
plt.plot(sim_results.data['time'].flatten(), sim_results.data['in_buf'].flatten(), 'r')
plt.plot(sim_results.data['time'].flatten(), sim_results.data['midn'].flatten(), 'k')
plt.plot(sim_results.data['time'].flatten(), sim_results.data['midp'].flatten(), 'c')
plt.plot(sim_results.data['time'].flatten(), sim_results.data['out'].flatten(), 'm')
plt.legend(['in', 'inb_buf', 'in_buf', 'midn', 'midp', 'out'])
plt.title(f'pseg_off: {pseg_off}, pseg: {inv_pseg}, nseg: {inv_nseg-pseg_off}, fanout: {fanout}')
plt.show(block=False)
'''
# Error checking
if math.isinf(np.max(tdr_cur)) or math.isinf(np.max(tdf_cur)):
raise ValueError("Got infinite delay!")
if np.min(tdr_cur) < 0 or np.min(tdf_cur) < 0:
raise ValueError("Got negative delay.")
err_cur = np.abs(tdr_cur[0] - tdf_cur[0])
if err_cur > err_worst:
err_worst = err_cur
worst_env = env
tdr = tdr_cur[0]
tdf = tdf_cur[0]
'''
print(f'iter: {inv_pseg}')
print(f'env: {worst_env}, tdr: {tdr}, tdf: {tdf}')
breakpoint()
'''
if tdr < tdf:
iterator.down(tdr - tdf)
else:
iterator.up(tdr - tdf)
err_abs = np.abs(tdr - tdf)
if err_abs < err_best:
err_best = err_abs
iterator.save_info(pseg_off)
pseg_off = iterator.get_last_save_info()
pseg_off = 0 if pseg_off is None else pseg_off # Should only hit this case if inv_pseg_nom = 1
inv_pseg = inv_pseg_nom + pseg_off
return inv_pseg, inv_nseg - 0 * pseg_off
async def _design_lvl_shift_inv_pdn(self, pseg: int, nseg: int,
out_inv_m: int, fanout: float,
pinfo: Any, tbm_specs: Dict[str, Any],
has_rst, dual_output, vin,
vout) -> int:
"""
This function figures out the NMOS nseg for the inverter given the target delay
TODO: Make this use digitaldB instead
"""
min_fanout: float = get_tech_global_info('bag3_digital')['min_fanout']
inv_beta: float = get_tech_global_info('bag3_digital')['inv_beta']
tb_params = self._get_full_tb_params()
# Use a binary iterator to find the NMOS size
max_nseg = int(np.round(nseg / min_fanout))
iterator = BinaryIterator(1, max_nseg)
load_seg = nseg + (pseg if has_rst else 0)
inv_pseg = int(
np.round(inv_beta * load_seg / ((1 + inv_beta) * fanout)))
inv_pseg = 1 if inv_pseg == 0 else inv_pseg
all_corners = get_tech_global_info(
'bag3_digital')['signoff_envs']['all_corners']
while iterator.has_next():
inv_nseg = iterator.get_next()
inv_in_nseg, inv_in_pseg = self._size_input_inv_for_fanout(
inv_pseg, inv_nseg, pseg, nseg, fanout, has_rst)
dut_params = self._get_lvl_shift_params_dict(
pinfo, pseg, nseg, inv_pseg, inv_nseg, inv_in_pseg,
inv_in_nseg, out_inv_m, has_rst, dual_output)
dut = await self.async_new_dut('lvshift', STDCellWrapper,
dut_params)
err_worst = -1 * float('Inf')
for env in all_corners['envs']:
tbm_specs['sim_envs'] = [env]
tbm_specs['sim_params']['vdd_in'] = all_corners[vin][env]
tbm_specs['sim_params']['vdd'] = all_corners[vout][env]
tbm = cast(CombLogicTimingTB,
self.make_tbm(CombLogicTimingTB, tbm_specs))
sim_results = await self.async_simulate_tbm_obj(
f'sim_inv_nseg_{inv_nseg}_{env}', dut, tbm, tb_params)
tdr_cur, tdf_cur = CombLogicTimingTB.get_output_delay(
sim_results.data,
tbm.specs,
'inb_buf',
'in_buf',
True,
in_pwr='vdd_in',
out_pwr='vdd_in')
target_cur, _ = CombLogicTimingTB.get_output_delay(
sim_results.data,
tbm.specs,
'inb_buf',
'midp',
True,
in_pwr='vdd_in',
out_pwr='vdd')
# Check for error conditions
if math.isinf(np.max(tdr_cur)) or math.isinf(
np.max(tdf_cur)) or math.isinf(np.max(target_cur)):
raise ValueError(
"Got infinite delay in level shifter design script (sizing inverter NMOS)."
)
if np.min(tdr_cur) < 0 or np.min(target_cur) < 0:
raise ValueError(
"Got negative delay in level shifter design script (sizing inverter NMOS). "
)
err_cur = tdr_cur[0] - target_cur[0]
if err_cur > err_worst:
err_worst = err_cur
worst_env = env
tdr = tdr_cur[0]
target = target_cur[0]
'''
print(f'iter: {inv_nseg}')
print(f'env: {worst_env}, tdr: {tdr}, target: {target}')
'''
if tdr < target:
iterator.down(target - tdr)
iterator.save_info(inv_nseg)
else:
iterator.up(target - tdr)
tmp_inv_nseg = iterator.get_last_save_info()
if tmp_inv_nseg is None:
tmp_inv_nseg = max_nseg
self.warn(
"Could not size pull down of inverter to meet required delay, picked the "
"max inv_nseg based on min_fanout.")
return tmp_inv_nseg
async def _design_lvl_shift_inv_pun(self, pseg: int, nseg: int,
inv_nseg: int, out_inv_m: int,
fanout: float, pinfo: Any,
tbm_specs: Dict[str, Any], has_rst,
dual_output, vin,
vout) -> Tuple[int, int]:
"""
Given the NMOS pull down size, this function will design the PMOS pull up so that the delay
mismatch is minimized.
"""
inv_beta = get_tech_global_info('bag3_digital')['inv_beta']
tb_params = self._get_full_tb_params()
# Use a binary iterator to find the PMOS size
load_seg = nseg + (pseg if has_rst else 0)
inv_pseg_nom = int(
np.round(inv_beta * load_seg / ((1 + inv_beta) * fanout)))
inv_pseg_nom = 1 if inv_pseg_nom == 0 else inv_pseg_nom
inv_nseg_nom = inv_nseg # save the value of nseg coming into this function as nominal
range_to_vary = min(inv_pseg_nom, inv_nseg)
iterator = BinaryIterator(
-range_to_vary + 1,
1) # upper limit is exclusive hence using 1 instead of 0
# variation will be done such that the total P+N segments remains the same
# This allows the input inverter sizing to be done once at the start
# iterator = BinaryIterator(-inv_pseg_nom+1, 0)
# iterator = BinaryIteratorInterval(get_tech_global_info('bag3_digital')['width_interval_list_p'],
# -inv_pseg_nom+1, 0)
err_best = float('inf')
inv_in_nseg, inv_in_pseg = self._size_input_inv_for_fanout(
inv_pseg_nom, inv_nseg, pseg, nseg, fanout, has_rst)
all_corners = get_tech_global_info(
'bag3_digital')['signoff_envs']['all_corners']
while iterator.has_next():
pseg_off = iterator.get_next()
inv_pseg = inv_pseg_nom + pseg_off
inv_nseg = inv_nseg_nom - pseg_off
dut_params = self._get_lvl_shift_params_dict(
pinfo, pseg, nseg, inv_pseg, inv_nseg, inv_in_pseg,
inv_in_nseg, out_inv_m, has_rst, dual_output)
dut = await self.async_new_dut('lvshift', STDCellWrapper,
dut_params)
err_worst = -1 * float('Inf')
for env in all_corners['envs']:
tbm_specs['sim_envs'] = [env]
tbm_specs['sim_params']['vdd_in'] = all_corners[vin][env]
tbm_specs['sim_params']['vdd'] = all_corners[vout][env]
tbm = cast(CombLogicTimingTB,
self.make_tbm(CombLogicTimingTB, tbm_specs))
sim_results = await self.async_simulate_tbm_obj(
f'sim_inv_pseg_{inv_pseg}_{env}', dut, tbm, tb_params)
tdr_cur, tdf_cur = CombLogicTimingTB.get_output_delay(
sim_results.data,
tbm.specs,
'in',
'out',
False,
in_pwr='vdd_in',
out_pwr='vdd')
print("Balance rise/fall delays inv_pup Info: ", env, tdr_cur,
tdf_cur)
# Error checking
if math.isinf(np.max(tdr_cur)) or math.isinf(np.max(tdf_cur)):
raise ValueError("Got infinite delay!")
if np.min(tdr_cur) < 0 or np.min(tdf_cur) < 0:
raise ValueError("Got negative delay.")
err_cur = np.abs(tdr_cur[0] - tdf_cur[0])
if err_cur > err_worst:
err_worst = err_cur
worst_env = env
tdr = tdr_cur[0]
tdf = tdf_cur[0]
if tdr < tdf:
iterator.down(tdr - tdf)
else:
iterator.up(tdr - tdf)
err_abs = np.abs(tdr - tdf)
if err_abs < err_best:
err_best = err_abs
iterator.save_info(pseg_off)
pseg_off = iterator.get_last_save_info()
pseg_off = 0 if pseg_off is None else pseg_off # Should only hit this case if inv_pseg_nom = 1
inv_pseg = inv_pseg_nom + pseg_off
inv_nseg = inv_nseg_nom - pseg_off
return inv_pseg, inv_nseg - 0 * pseg_off
