def get_cnum(self, vdd):
core = self.core
core_power = core.power(vdd)
_debug(_bm_('core_power: {0}', core_power))
l2_power = self.l2_traits['power']
l2_area = self.l2_traits['area']
_debug(_bm_('l2_power: {0}', l2_power))
l1_power = self.l1_traits['power']
l1_area = self.l1_traits['area']
_debug(_bm_('l1_power: {0}', l1_power))
cnum = min((self.sys_power - l2_power) / (core_power + l1_power),
(self.sys_area - l2_area) / (core.area + l1_area))
return int(cnum)
def get_cnum(self, vdd):
core = self.core
core_power = core.power(vdd)
_debug(_bm_('core_power: {0}', core_power))
l2_power = self.l2_traits['power']
l2_area = self.l2_traits['area']
_debug(_bm_('l2_power: {0}', l2_power))
l1_power = self.l1_traits['power']
l1_area = self.l1_traits['area']
_debug(_bm_('l1_power: {0}', l1_power))
cnum = min((self.sys_power - l2_power) / (core_power + l1_power),
(self.sys_area - l2_area) / (core.area + l1_area))
return int(cnum)
def perf(self, vdd, app, cnum=None):
if app.type != 'synthetic':
raise HomogSysError('Requires a synthetic application')
if not cnum:
cnum = self.get_cnum(vdd)
_debug(_bm_('cnum: {0}', cnum))
core = self.core
_debug(_bm_('freq: {0}', core.freq(vdd)))
cov = 1
perf = 0
# kernels will be accelerated by multi-cores
for kid in app.get_all_kernels():
kcov = app.get_cov(kid)
kobj = app.get_kernel(kid)
miss_l1 = min(
1,
kobj.miss_l1 * ((self.cache_sz_l1 /
(kobj.cache_sz_l1_nom))**(1 - kobj.alpha_l1)))
miss_l2 = min(
1,
kobj.miss_l2 *
((self.cache_sz_l2 /
(cnum * kobj.cache_sz_l2_nom))**(1 - kobj.alpha_l2)))
_debug(_bm_('l1_miss: {0}, l2_miss: {1}', miss_l1, miss_l2))
t0 = ((1 - miss_l1) * self.delay_l1 + miss_l1 *
(1 - miss_l2) * self.delay_l2 +
miss_l1 * miss_l2 * self.delay_mem)
t = t0 * core.freq(vdd) / core.freq(core.vnom)
_debug(_bm_('t: {0}', t))
eta = 1 / (1 + t * kobj.rm / kobj.cpi_exe)
eta0 = 1 / (1 + t0 * kobj.rm / kobj.cpi_exe)
_debug(_bm_('eta: {0}, eta0: {1}', eta, eta0))
_debug(_bm_('freq: {0}, freq0: {1}', core.freq(vdd), core.fnom))
_debug(_bm_('vdd: {0}, v0: {1}', vdd, core.vnom))
p_speedup = (core.freq(vdd) / core.fnom) * cnum * (eta / eta0)
_debug(_bm_('p_speedup: {0}', p_speedup))
vdd_max = min(core.vnom * VSF_MAX, core.vmax)
s_speedup = 1
_debug(_bm_('s_speedup: {0}', s_speedup))
perf += kcov * ((1 - kobj.pf + kobj.pf / p_speedup))
cov -= kcov
# non-kernels will not be speedup
perf += cov
abs_perf = core.perfnom / perf # speedup = 1 / perf
return abs_perf
def __init__(self, budget, tech, serial_core=None, tput_core=None):
self.sys_area = budget.area
self.sys_power = budget.power
self._sys_bw = budget.bw
self.tech = tech
self.sys_bandwidth = self._sys_bw[tech]
# asic_dict[kid][acc_id] = Acc_obj
self.asic_dict = dict()
# asic_power_dict[kid][acc_id] = (power_max, power_min, power_nom)
self.asic_power_dict = dict()
if tput_core:
self.thru_core = tput_core
else:
self.thru_core = BaseCore(tech, 'cmos', 'hp', 'io')
self.dim_perf = None
self.serial_core = serial_core
if serial_core:
self.thru_core_area = self.sys_area - serial_core.area
_debug(
_bm_('Serial core: {0}, area: {1}', self.serial_core.ctype,
self.serial_core.area))
else:
self.thru_core_area = self.sys_area
self.use_gpacc = False
def __init__(self, budget, tech, serial_core=None, tput_core=None):
self.sys_area = budget.area
self.sys_power = budget.power
self._sys_bw = budget.bw
self.tech = tech
self.sys_bandwidth = self._sys_bw[tech]
# asic_dict[kid][acc_id] = Acc_obj
self.asic_dict = dict()
# asic_power_dict[kid][acc_id] = (power_max, power_min, power_nom)
self.asic_power_dict = dict()
if tput_core:
self.thru_core = tput_core
else:
self.thru_core = BaseCore(tech, 'cmos', 'hp', 'io')
self.dim_perf = None
self.serial_core = serial_core
if serial_core:
self.thru_core_area = self.sys_area - serial_core.area
_debug(_bm_('Serial core: {0}, area: {1}',
self.serial_core.ctype, self.serial_core.area))
else:
self.thru_core_area = self.sys_area
self.use_gpacc = False
def add_kernel(self, kernel, cov):
"""Register a kernel to be accelerate.
The kernel could be accelerated by certain ASIC, or more
generalized GPU/FPGA
Parameters
----------
kernel : :class:`~lumos.model.workload.kernel.Kernel`
The kernel object
cov : float
The coerage of the kernel, relative to the serial execution
Raises
------
AppError
the given coverage (cov) is larger than the overall parallel ratio
"""
name = kernel.name
if name in self.kernels:
_debug(_bm_('Kernel {0} already exist', name))
return False
if cov > self.f_noacc:
raise AppError(
'[add_kernel]: cov of {0} is too large to exceed the overall '
'parallel ratio {1}'.format(cov, self.f_noacc))
self.kernels[name] = kernel
self.kernels_coverage[name] = cov
self.f_noacc = self.f_noacc - cov
self.tag = self.tag_update()
def load_from_xmltree(cls, xmltree, kernels):
name = xmltree.get('name')
if not name:
raise AppError("No name in app config")
a = cls(name)
ps = xmltree.find('perf_config')
if ps is None:
raise Exception('No performance configuration in {0}'.format(name))
else:
for ele in ps:
if ele.tag is etree.Comment:
continue
setattr(a, ele.tag, float(ele.text))
ks = xmltree.find('kernel_config')
if ks is None:
_debug(_bm_('No kernel config in {0}', name))
else:
for ele in ks:
kname = ele.get('name')
if not kname:
raise Exception('No name for kernel {0} in app {1}'.format(
kname, name))
val_ = ele.get('cov')
if not val_:
raise Exception(
'No covreage for kernel {0} in app {1}'.format(
kname, name))
k_cov = float(val_)
a_.add_kernel(kernels[kname], k_cov)
return a
def _dim_perf_opt(self, power_budget=None, cnum_max=None):
"""Get the optimal performance of multicore, subjecting to power and area budget.
Increasing the number of cores can improve throughput, while a stringent
system budget (e.g. power and area) may limit the throughput improvement.
This method finds the optimal throughput-based performance.
Parameters
----------
power_budget : float
power budget, if None, system power budget will be used
cnum_max : int
maximum core number, if None, system area budget will be used to determine cnum_max
Returns
-------
perf : float
optimal throughput-based performance
vdd : int
supply voltage when achieving the optimal throughput
cnum : int
the number of active cores when achieving the optimal throughput
power_eff : float
the effective power of throughput cores
"""
core = self.thru_core
if not cnum_max:
cnum_max = int(self.sys_area / core.area)
_debug(_bm_('power budget: {0}', power_budget))
perf_opt, vdd_opt, cnum_opt, power_eff = 0, 0, 0, 0
for cnum in range(1, cnum_max + 1):
perf_, vdd_, power_ = self._dim_perf_cnum(
cnum, power_budget=power_budget)
if perf_ == 0:
# power budget is too small to power such many cores
break
if perf_ > perf_opt:
perf_opt = perf_
vdd_opt = vdd_
cnum_opt = cnum
power_eff = power_
_debug(
_bm_('cnum: {0}, perf_opt: {1}, power_eff: {2}', cnum,
perf_opt, power_eff))
return (perf_opt, vdd_opt, cnum_opt, power_eff)
def perf(self, vdd, app, cnum=None):
if app.type != 'synthetic':
raise HomogSysError('Requires a synthetic application')
if not cnum:
cnum = self.get_cnum(vdd)
_debug(_bm_('cnum: {0}', cnum))
core = self.core
_debug(_bm_('freq: {0}', core.freq(vdd)))
cov = 1
perf = 0
# kernels will be accelerated by multi-cores
for kid in app.get_all_kernels():
kcov = app.get_cov(kid)
kobj = app.get_kernel(kid)
miss_l1 = min(
1, kobj.miss_l1 * ((self.cache_sz_l1 /
(kobj.cache_sz_l1_nom)) **
(1 - kobj.alpha_l1)))
miss_l2 = min(
1, kobj.miss_l2 * ((self.cache_sz_l2 /
(cnum * kobj.cache_sz_l2_nom)) **
(1 - kobj.alpha_l2)))
_debug(_bm_('l1_miss: {0}, l2_miss: {1}', miss_l1, miss_l2))
t0 = ((1 - miss_l1) * self.delay_l1 + miss_l1 * (1 - miss_l2) *
self.delay_l2 + miss_l1 * miss_l2 * self.delay_mem)
t = t0 * core.freq(vdd) / core.freq(core.vnom)
_debug(_bm_('t: {0}', t))
eta = 1 / (1 + t * kobj.rm / kobj.cpi_exe)
eta0 = 1 / (1 + t0 * kobj.rm / kobj.cpi_exe)
_debug(_bm_('eta: {0}, eta0: {1}', eta, eta0))
_debug(_bm_('freq: {0}, freq0: {1}', core.freq(vdd), core.fnom))
_debug(_bm_('vdd: {0}, v0: {1}', vdd, core.vnom))
p_speedup = (core.freq(vdd) / core.fnom) * cnum * (eta / eta0)
_debug(_bm_('p_speedup: {0}', p_speedup))
vdd_max = min(core.vnom * VSF_MAX, core.vmax)
s_speedup = 1
_debug(_bm_('s_speedup: {0}', s_speedup))
perf += kcov * ((1 - kobj.pf + kobj.pf / p_speedup))
cov -= kcov
# non-kernels will not be speedup
perf += cov
abs_perf = core.perfnom / perf # speedup = 1 / perf
return abs_perf
def _dim_perf_opt(self, power_budget=None, cnum_max=None):
"""Get the optimal performance of multicore, subjecting to power and area budget.
Increasing the number of cores can improve throughput, while a stringent
system budget (e.g. power and area) may limit the throughput improvement.
This method finds the optimal throughput-based performance.
Parameters
----------
power_budget : float
power budget, if None, system power budget will be used
cnum_max : int
maximum core number, if None, system area budget will be used to determine cnum_max
Returns
-------
perf : float
optimal throughput-based performance
vdd : int
supply voltage when achieving the optimal throughput
cnum : int
the number of active cores when achieving the optimal throughput
power_eff : float
the effective power of throughput cores
"""
core = self.thru_core
if not cnum_max:
cnum_max = int(self.sys_area / core.area)
_debug(_bm_('power budget: {0}', power_budget))
perf_opt, vdd_opt, cnum_opt, power_eff = 0, 0, 0, 0
for cnum in range(1, cnum_max + 1):
perf_, vdd_, power_ = self._dim_perf_cnum(cnum, power_budget=power_budget)
if perf_ == 0:
# power budget is too small to power such many cores
break
if perf_ > perf_opt:
perf_opt = perf_
vdd_opt = vdd_
cnum_opt = cnum
power_eff = power_
_debug(_bm_('cnum: {0}, perf_opt: {1}, power_eff: {2}',
cnum, perf_opt, power_eff))
return (perf_opt, vdd_opt, cnum_opt, power_eff)
def get_speedup_appdag_serial(self, appdag):
"""Get the performance of the system, on an :class:`~lumos.model.AppDAG`
application, all kernels are processed in serial.
Parameters
----------
appdag : :class:`~lumos.model.AppDAG`
The target application
Returns
-------
float
speedup relative to running all kernels at the baseline performance.
"""
dim_perf, opt_vdd, opt_cnum, power_eff = self._dim_perf_opt(
power_budget=self.sys_power)
thru_core = self.thru_core
thrucore_serial_su = thru_core.perf_by_vdd(opt_vdd) / PERF_BASE
thrucore_thru_su = dim_perf / PERF_BASE
_debug(
_bm_('thrucore serial su: {0}, thrucore parallel su: {1}',
thrucore_serial_su, thrucore_thru_su))
serial_su = thru_core.perf_by_vdd(thru_core.vnom) / PERF_BASE
_debug(_bm_('serial su: {0}', serial_su))
ker_lengths = appdag.get_all_kernel_lengths()
ker_objs = appdag.get_all_kernels(mode='object')
_debug(
_bm_('dim_perf: {0} cnum: {1}, vdd: {2}', dim_perf, opt_cnum,
opt_vdd))
baseline = sum(ker_lengths)
perf = 0
for kl, ko in zip(ker_lengths, ker_objs):
_debug(_bm_('-------{0}---------', ko.name))
if self.has_asacc(ko.name):
acc = self.get_asacc(ko.name)
rt = kl / acc.perf()
_debug(_bm_('Accelerator speedup: {0}', acc.perf()))
else:
if ko.pf == 0:
# this is a serial application
rt = kl / serial_su
else:
# this is a parallel application
rt = kl * (
1 - ko.pf
) / thrucore_serial_su + kl * ko.pf / thrucore_thru_su
perf += rt
_debug(_bm_('runtime: {0}, accu runtime: {1}', rt, perf))
_debug(_bm_('baseline: {0}, bench: {1}', baseline, perf))
return baseline / perf
def load_from_xmltree(cls, xmltree, kernels):
name = xmltree.get('name')
if not name:
raise AppError("No name in app config")
a = cls(name)
ks = xmltree.find('kernel_config')
if ks is None:
_debug(_bm_('No kernel config in {0}', name))
else:
for ele in ks:
kname = ele.get('name')
if not kname:
raise Exception('No name for kernel {0} in app {1}'.format(
kname, name))
val_ = ele.get('cov')
if not val_:
raise Exception(
'No covreage for kernel {0} in app {1}'.format(
kname, name))
k_cov = float(val_)
val_ = ele.get('rc_count')
if not val_:
k_rc_count = 1
else:
k_rc_count = int(val_)
val_ = ele.get('rc_time')
if not val_:
k_rc_time = 0
else:
k_rc_time = float(val_)
a.add_kernel(kernels[kname], k_cov, k_rc_count, k_rc_time)
_debug(
_bm_('Add kernel {0}, cov {1}, rc_count {2}, rc_time {3}',
kname, k_cov, k_rc_count, k_rc_time))
return a
def get_speedup_appdag_serial(self, appdag):
"""Get the performance of the system, on an :class:`~lumos.model.AppDAG`
application, all kernels are processed in serial.
Parameters
----------
appdag : :class:`~lumos.model.AppDAG`
The target application
Returns
-------
float
speedup relative to running all kernels at the baseline performance.
"""
dim_perf, opt_vdd, opt_cnum, power_eff = self._dim_perf_opt(power_budget=self.sys_power)
thru_core = self.thru_core
thrucore_serial_su = thru_core.perf_by_vdd(opt_vdd) / PERF_BASE
thrucore_thru_su = dim_perf / PERF_BASE
_debug(_bm_('thrucore serial su: {0}, thrucore parallel su: {1}',
thrucore_serial_su, thrucore_thru_su))
serial_su = thru_core.perf_by_vdd(thru_core.vnom) / PERF_BASE
_debug(_bm_('serial su: {0}', serial_su))
ker_lengths = appdag.get_all_kernel_lengths()
ker_objs = appdag.get_all_kernels(mode='object')
_debug(_bm_('dim_perf: {0} cnum: {1}, vdd: {2}',
dim_perf, opt_cnum, opt_vdd))
baseline = sum(ker_lengths)
perf = 0
for kl, ko in zip(ker_lengths, ker_objs):
_debug(_bm_('-------{0}---------', ko.name))
if self.has_asacc(ko.name):
acc = self.get_asacc(ko.name)
rt = kl / acc.perf()
_debug(_bm_('Accelerator speedup: {0}', acc.perf()))
else:
if ko.pf == 0:
# this is a serial application
rt = kl / serial_su
else:
# this is a parallel application
rt = kl * (1-ko.pf)/thrucore_serial_su + kl * ko.pf/thrucore_thru_su
perf += rt
_debug(_bm_('runtime: {0}, accu runtime: {1}', rt, perf))
_debug(_bm_('baseline: {0}, bench: {1}', baseline, perf))
return baseline / perf
def _dim_perf_cnum(self, cnum, vmin=None, power_budget=None):
"""Get the performance by given the active number of cores.
Given number of multi-cores (potentially) running at lower supply voltage.
Parameters
----------
cnum : int
The number of active cores
vmin : float, optional
The minimum voltage of cores
power_budget : float
The power budget, if None, system power budget will be used
Returns
-------
perf : float
The performance score, not relative speedup
vdd : int
The supply voltage in mV, when the system achieves the optimal
throughput
power : float
The effective power conumption of dim cores. If it is less than the
provided power_budget, this usually means the performance is
constrained by area_budget instead of power_budget
"""
core = self.thru_core
if not power_budget:
power_budget = self.sys_power
cpower = power_budget / float(cnum)
if not vmin:
vmin = core.vmin
elif vmin < core.vmin:
_debug(_bm_('Provided vmin {0}mV is lower than core.vmin {1}mV. '
'vmin is set to core.vmin', vmin, core.vmin))
vmin = core.vmin
# first check whether vmin can meet the power constraint. If not,
# it is probabaly either due to vmin is too high, or power budget
# is too constrained, return None in this case.
if core.power(vmin) > cpower:
_debug(_bm_('Power budget {1:.3g}W is not met even at vmin of {0}mV',
vmin, power_budget))
return (0, 0, 0)
# use binary search to find the highest per-core vdd that stays within the power_budget
vmax = core.vmax
while vmax > vmin:
vmid = math.ceil((vmin+vmax) / 2)
power_vmid = core.power(vmid)
if power_vmid > cpower:
vmax = vmid - 1
else:
vmin = vmid
perf_opt = cnum * core.perf_by_vdd(vmin)
power_eff = cnum * core.power(vmin)
return (perf_opt, vmin, power_eff)
def perf_by_cnum(self, cnum, app, vmin=None):
"""
Get the relative performance of the system for a given application, with a
given constraint on the number of active cores.
Parameters
----------
cnum: num
The number of core required to be active.
app: :class:`~lumos.model.application.Application`
The targeted application.
vmin: num
An optional argument to specify the lowest boundary which supply
voltage can be scaled down.
Returns
-------
dict: results wrapped in a python dict with three keys:
perf : num
The relatvie performance.
vdd : num
The supply voltage of the optimal configuration under core number
constraint.
freq : num
The frequency with the optimal configuration under core number
constraint.
cnum : num
The actual number of active cores, if the requried number can not be met.
util : num
The utilization of the system at the optimal configuraiton.
"""
core = self.core
f = app.f
cnum_max = int(self.area / core.area)
if cnum > cnum_max or cnum < 0:
return None
cpower = self.power / float(cnum)
_debug(_bm_('Per-core power budget: {0}', cpower))
# Serial performance is achieved by the highest vdd
sperf = core.perf_by_vdd(core.vmax)
if not vmin:
vmin = core.vmin
# Check whether vmin can meet the power requirement
if vmin >= core.vmin:
if core.power(vmin) > cpower:
# Either vmin is too high or active_cnum is too large
# so that the system could not meet the power budget even
# with the minimum vdd. Return the active core number with vmin
# Users can capture the exception by comparing the active_cnum
# and the returned active_cnum
active_cnum = min(int(self.area / core.area),
int(self.power / core.power(vmin)))
perf = 1 / ((1 - f) / sperf + f /
(active_cnum * core.perf_by_vdd(vmin)))
util = float(100 * active_cnum) / float(cnum)
_debug(_bm_('vmin is too high or active_cnum is too large'))
return {
'perf': perf / PERF_BASE,
'vdd': vmin,
'cnum': active_cnum,
'freq': core.freq(vmin),
'util': util
}
else:
vmin = core.vmin
vl = vmin
vr = core.vmax
vm = int((vl + vr) / 2)
while (vr - vl) > V_PRECISION:
vm = int((vl + vr) / 2)
_debug(
_bm_(
'[Core]\t:vl: {0}mV, vr: {1}mV, vm: {2}mV, '
'freq: {3}, power: {4}, area: {5}', vl, vr, vm,
core.freq(vm), core.power(vm), core.area))
if core.power(vm) > cpower:
vl = vl
vr = vm
else:
vl = vm
vr = vr
_debug(_bm_('End of bin-search, vl: {0}mV, vr: {1}mV', vl, vr))
core.vdd = vl
lpower = core.power(vl)
lfreq = core.freq(vl)
lcnum = min(int(self.area / core.area), int(self.power / lpower))
lperf = 1 / ((1 - f) / sperf + f / (cnum * core.perf_by_vdd(vl)))
rpower = core.power(vr)
rfreq = core.freq(vr)
rcnum = min(int(self.area / core.area), int(self.power / rpower))
rperf = 1 / ((1 - f) / sperf + f / (cnum * core.perf_by_vdd(vr)))
if rpower <= cpower:
# right bound meets the power constraint
return {
'perf': rperf / PERF_BASE,
'vdd': vr,
'cnum': cnum,
'freq': rfreq,
'util': float(100 * cnum) / float(cnum_max)
}
else:
return {
'perf': lperf / PERF_BASE,
'vdd': vl,
'freq': lfreq,
'cnum': cnum,
'util': float(100 * cnum) / float(cnum_max)
}
if mo:
return int(mo.group(1))
else:
raise TechModelError('no technology node from the name of {0}'.format(model_file))
model_name = 'homoTFET30nm'
freq_dict = dict()
dynamic_power_dict = dict()
static_power_dict = dict()
model_files = glob.glob(os.path.join(
_MODEL_DIR, '{0}_{1}_*.data'.format(
settings.TFET_SIM_CIRCUIT, model_name)))
for model_file in model_files:
_debug(_bm_('found model {0}', model_file))
model_file_mtime = os.path.getmtime(model_file)
tech = _get_tech_node(model_file)
pickle_file = os.path.join(
_MODEL_DIR, '{0}_{1}_{2}.p'.format(
settings.TFET_SIM_CIRCUIT, model_name, tech))
try:
pickle_file_mtime = os.path.getmtime(pickle_file)
except OSError:
pickle_file_mtime = 0
if pickle_file_mtime > model_file_mtime:
with open(pickle_file, 'rb') as f:
freq_dict[tech] = pickle.load(f)
dynamic_power_dict[tech] = pickle.load(f)
def instantiate(self):
self._thru_core_num = int(self.thru_core_area / self.thru_core.area)
_debug(
_bm_('Tput core: {0}, area: {1}, cnum: {2}', self.thru_core.ctype,
self.thru_core.area, self._thru_core_num))
def _dim_perf_cnum(self, cnum, vmin=None, power_budget=None):
"""Get the performance by given the active number of cores.
Given number of multi-cores (potentially) running at lower supply voltage.
Parameters
----------
cnum : int
The number of active cores
vmin : float, optional
The minimum voltage of cores
power_budget : float
The power budget, if None, system power budget will be used
Returns
-------
perf : float
The performance score, not relative speedup
vdd : int
The supply voltage in mV, when the system achieves the optimal
throughput
power : float
The effective power conumption of dim cores. If it is less than the
provided power_budget, this usually means the performance is
constrained by area_budget instead of power_budget
"""
core = self.thru_core
if not power_budget:
power_budget = self.sys_power
cpower = power_budget / float(cnum)
if not vmin:
vmin = core.vmin
elif vmin < core.vmin:
_debug(
_bm_(
'Provided vmin {0}mV is lower than core.vmin {1}mV. '
'vmin is set to core.vmin', vmin, core.vmin))
vmin = core.vmin
# first check whether vmin can meet the power constraint. If not,
# it is probabaly either due to vmin is too high, or power budget
# is too constrained, return None in this case.
if core.power(vmin) > cpower:
_debug(
_bm_('Power budget {1:.3g}W is not met even at vmin of {0}mV',
vmin, power_budget))
return (0, 0, 0)
# use binary search to find the highest per-core vdd that stays within the power_budget
vmax = core.vmax
while vmax > vmin:
vmid = math.ceil((vmin + vmax) / 2)
power_vmid = core.power(vmid)
if power_vmid > cpower:
vmax = vmid - 1
else:
vmin = vmid
perf_opt = cnum * core.perf_by_vdd(vmin)
power_eff = cnum * core.power(vmin)
return (perf_opt, vmin, power_eff)
def get_speedup_appdag_parallel_greedy(self, appdag):
"""Get the performance of the system, on an
:class:`~lumos.model.AppDAG` application, all kernels are
processed in parallel, power budget is allocated to accelerators
in a greedy way.
The system power budget will be allocated to the kernel that has
the longest execution time, the power of the accelerator working
at nominal supply will be deducted from the system budget. Then
the system will try to allocate the remaining power budget to
the accelerator targeting the next longest running kernel. Until
there is no more accelerators can be activate.
This will assume that all parallel kernels are supported by accelerators.
Parameters
----------
appdag : :class:`~lumos.model.AppDAG`
The target application
Returns
-------
float
speedup relative to running all kernels at the baseline performance.
"""
ker_lengths = appdag.get_all_kernel_lengths()
baseline = sum(ker_lengths)
depth_sorted = appdag.kernels_depth_sort()
finish = 0
for l, node_list in enumerate(depth_sorted):
ker_lengths = [
appdag.get_kernel_length(idx_) for idx_ in node_list
]
ker_len_sorted = sorted(zip(ker_lengths, node_list), reverse=True)
power_budget = self.sys_power
runtime = []
for kl, idx_ in ker_len_sorted:
ko = appdag.get_kernel(idx_)
if self.has_asacc(ko.name):
asacc = self.get_asacc(ko.name)
asacc_su = asacc.perf(power=power_budget) / PERF_BASE
power_budget -= asacc.power_eff
rt = kl / asacc_su
runtime.append(rt)
else:
perf_, vdd_, cnum_, power_eff = self._dim_perf_opt(
power_budget=power_budget)
if power_eff == 0:
# remaining power budget is too small
power_budget = 0
else:
thru_su = perf_ / PERF_BASE
serial_su = self.thru_core.perf_by_vdd(
vdd_) / PERF_BASE
power_budget -= power_eff
rt = kl * (1 -
ko.pf) / serial_su + kl * ko.pf / thru_su
runtime.append(rt)
_debug(_bm_('runtime: {0}', rt))
if power_budget <= 0.1:
finish += max(runtime)
_debug(_bm_('=====warp finish====='))
_debug(_bm_('run time of this warp: {0}', max(runtime)))
runtime = []
power_budget = self.sys_power
if runtime:
finish += max(runtime)
_debug(_bm_('=====warp finish====='))
_debug(_bm_('run time of this warp: {0}', max(runtime)))
_debug(_bm_('baseline: {0}, bench: {1}', baseline, finish))
return baseline / finish
def get_speedup_appdag_parallel_greedy(self, appdag):
"""Get the performance of the system, on an
:class:`~lumos.model.AppDAG` application, all kernels are
processed in parallel, power budget is allocated to accelerators
in a greedy way.
The system power budget will be allocated to the kernel that has
the longest execution time, the power of the accelerator working
at nominal supply will be deducted from the system budget. Then
the system will try to allocate the remaining power budget to
the accelerator targeting the next longest running kernel. Until
there is no more accelerators can be activate.
This will assume that all parallel kernels are supported by accelerators.
Parameters
----------
appdag : :class:`~lumos.model.AppDAG`
The target application
Returns
-------
float
speedup relative to running all kernels at the baseline performance.
"""
ker_lengths = appdag.get_all_kernel_lengths()
baseline = sum(ker_lengths)
depth_sorted = appdag.kernels_depth_sort()
finish = 0
for l, node_list in enumerate(depth_sorted):
ker_lengths = [appdag.get_kernel_length(idx_) for idx_ in node_list]
ker_len_sorted = sorted(zip(ker_lengths, node_list), reverse=True)
power_budget = self.sys_power
runtime = []
for kl, idx_ in ker_len_sorted:
ko = appdag.get_kernel(idx_)
if self.has_asacc(ko.name):
asacc = self.get_asacc(ko.name)
asacc_su = asacc.perf(power=power_budget) / PERF_BASE
power_budget -= asacc.power_eff
rt = kl / asacc_su
runtime.append(rt)
else:
perf_, vdd_, cnum_, power_eff = self._dim_perf_opt(power_budget=power_budget)
if power_eff == 0:
# remaining power budget is too small
power_budget = 0
else:
thru_su = perf_ / PERF_BASE
serial_su = self.thru_core.perf_by_vdd(vdd_) / PERF_BASE
power_budget -= power_eff
rt = kl * (1-ko.pf)/serial_su + kl * ko.pf / thru_su
runtime.append(rt)
_debug(_bm_('runtime: {0}', rt))
if power_budget <= 0.1:
finish += max(runtime)
_debug(_bm_('=====warp finish====='))
_debug(_bm_('run time of this warp: {0}', max(runtime)))
runtime = []
power_budget = self.sys_power
if runtime:
finish += max(runtime)
_debug(_bm_('=====warp finish====='))
_debug(_bm_('run time of this warp: {0}', max(runtime)))
_debug(_bm_('baseline: {0}, bench: {1}', baseline, finish))
return baseline / finish
def instantiate(self):
self._thru_core_num = int(self.thru_core_area / self.thru_core.area)
_debug(_bm_('Tput core: {0}, area: {1}, cnum: {2}',
self.thru_core.ctype, self.thru_core.area, self._thru_core_num))
raise TechModelError(
'no technology node from the name of {0}'.format(model_file))
model_name = 'homoTFET30nm'
freq_dict = dict()
dynamic_power_dict = dict()
static_power_dict = dict()
model_files = glob.glob(
os.path.join(
_MODEL_DIR, '{0}_{1}_*.data'.format(settings.TFET_SIM_CIRCUIT,
model_name)))
for model_file in model_files:
_debug(_bm_('found model {0}', model_file))
model_file_mtime = os.path.getmtime(model_file)
tech = _get_tech_node(model_file)
pickle_file = os.path.join(
_MODEL_DIR, '{0}_{1}_{2}.p'.format(settings.TFET_SIM_CIRCUIT,
model_name, tech))
try:
pickle_file_mtime = os.path.getmtime(pickle_file)
except OSError:
pickle_file_mtime = 0
if pickle_file_mtime > model_file_mtime:
with open(pickle_file, 'rb') as f:
freq_dict[tech] = pickle.load(f)
dynamic_power_dict[tech] = pickle.load(f)
def perf_by_cnum(self, cnum, app, vmin=None):
"""
Get the relative performance of the system for a given application, with a
given constraint on the number of active cores.
Parameters
----------
cnum: num
The number of core required to be active.
app: :class:`~lumos.model.application.Application`
The targeted application.
vmin: num
An optional argument to specify the lowest boundary which supply
voltage can be scaled down.
Returns
-------
dict: results wrapped in a python dict with three keys:
perf : num
The relatvie performance.
vdd : num
The supply voltage of the optimal configuration under core number
constraint.
freq : num
The frequency with the optimal configuration under core number
constraint.
cnum : num
The actual number of active cores, if the requried number can not be met.
util : num
The utilization of the system at the optimal configuraiton.
"""
core = self.core
f = app.f
cnum_max = int(self.area / core.area)
if cnum > cnum_max or cnum < 0:
return None
cpower = self.power / float(cnum)
_debug(_bm_('Per-core power budget: {0}', cpower))
# Serial performance is achieved by the highest vdd
sperf = core.perf_by_vdd(core.vmax)
if not vmin:
vmin = core.vmin
# Check whether vmin can meet the power requirement
if vmin >= core.vmin:
if core.power(vmin) > cpower:
# Either vmin is too high or active_cnum is too large
# so that the system could not meet the power budget even
# with the minimum vdd. Return the active core number with vmin
# Users can capture the exception by comparing the active_cnum
# and the returned active_cnum
active_cnum = min(int(self.area / core.area),
int(self.power / core.power(vmin)))
perf = 1 / ((1 - f) / sperf + f /
(active_cnum * core.perf_by_vdd(vmin)))
util = float(100 * active_cnum) / float(cnum)
_debug(_bm_('vmin is too high or active_cnum is too large'))
return {
'perf': perf / PERF_BASE,
'vdd': vmin,
'cnum': active_cnum,
'freq': core.freq(vmin),
'util': util
}
else:
vmin = core.vmin
vl = vmin
vr = core.vmax
vm = int((vl + vr) / 2)
while (vr - vl) > V_PRECISION:
vm = int((vl + vr) / 2)
_debug(_bm_('[Core]\t:vl: {0}mV, vr: {1}mV, vm: {2}mV, '
'freq: {3}, power: {4}, area: {5}', vl, vr, vm,
core.freq(vm), core.power(vm), core.area))
if core.power(vm) > cpower:
vl = vl
vr = vm
else:
vl = vm
vr = vr
_debug(_bm_('End of bin-search, vl: {0}mV, vr: {1}mV', vl, vr))
core.vdd = vl
lpower = core.power(vl)
lfreq = core.freq(vl)
lcnum = min(int(self.area / core.area), int(self.power / lpower))
lperf = 1 / ((1 - f) / sperf + f / (cnum * core.perf_by_vdd(vl)))
rpower = core.power(vr)
rfreq = core.freq(vr)
rcnum = min(int(self.area / core.area), int(self.power / rpower))
rperf = 1 / ((1 - f) / sperf + f / (cnum * core.perf_by_vdd(vr)))
if rpower <= cpower:
# right bound meets the power constraint
return {
'perf': rperf / PERF_BASE,
'vdd': vr,
'cnum': cnum,
'freq': rfreq,
'util': float(100 * cnum) / float(cnum_max)
}
else:
return {
'perf': lperf / PERF_BASE,
'vdd': vl,
'freq': lfreq,
'cnum': cnum,
'util': float(100 * cnum) / float(cnum_max)
}
