def is_schedulable(no_cpus, tasks):
"""Simple utilization bound: tasks.utilization() <= no_cpus.
Assumption: all parameters are quantum multiples and deadlines
are not constrained.
"""
return tasks.utilization() <= no_cpus and \
forall(tasks)(lambda t: t.deadline >= t.period >= t.cost)
def is_schedulable(no_cpus, tasks):
"""Simple utilization bound: tasks.utilization() <= no_cpus.
Assumption: all parameters are quantum multiples and deadlines
are not constrained.
"""
return tasks.utilization() <= no_cpus and \
forall(tasks)(lambda t: t.deadline >= t.period >= t.cost)
def is_schedulable_py(
no_cpus, tasks, rta_min_step=1, want_baruah=3000, want_rta=True, want_ffdbf=False, want_load=False
):
if tasks.utilization() > no_cpus or not forall(tasks)(lambda t: t.period >= t.cost):
# trivially infeasible
return False
else:
not_arbitrary = tasks.only_constrained_deadlines()
if no_cpus == 1 and tasks.density() <= 1:
# simply uniprocessor density condition
return True
elif no_cpus > 1:
# Baker's test can handle arbitrary deadlines.
if bak_test(no_cpus, tasks):
return True
# The other tests cannot.
if not_arbitrary:
# The density test is cheap, try it first.
if gfb_test(no_cpus, tasks):
return True
# Ok, try the slower ones.
if should_use_baruah_test(want_baruah, tasks, no_cpus) and bar_test(no_cpus, tasks):
return True
if want_rta and rta_test(no_cpus, tasks, min_fixpoint_step=rta_min_step):
return True
# FF-DBF is almost always too slow.
if want_ffdbf and ffdbf_test(no_cpus, tasks):
return True
# If we get here, none of the tests passed.
return False
def is_schedulable(m, tasks):
"""Are the given tasks schedulable on m processors?"""
if tasks.utilization() >= m or not forall(tasks)(lambda t: t.constrained_deadline()):
return False
for (tsk_k, a_k_bound) in izip(tasks, ak_bounds(tasks, m)):
for a_k in tasks.dbf_points_of_change(a_k_bound, offset=tsk_k.deadline):
if not task_schedulable_for_offset(tasks, tsk_k, a_k, m):
return False
return True
def is_schedulable(m, tasks):
"""Are the given tasks schedulable on m processors?"""
if tasks.utilization() >= m or not forall(tasks)(lambda t: t.constrained_deadline()):
return False
for (tsk_k, a_k_bound) in izip(tasks, ak_bounds(tasks, m)):
for a_k in all_dbf_points_of_change_dk(tasks, a_k_bound, tsk_k.deadline):
if not task_schedulable_for_offset(tasks, tsk_k, a_k, m):
return False
return True
def bound_response_times(no_cpus, tasks, preemptive=True):
# DA's work applies to implicit-deadline tasks
assert forall(tasks)(lambda t: t.implicit_deadline())
x = task_tardiness_bound(no_cpus, tasks, preemptive)
if x is None:
return False
else:
for t in tasks:
t.response_time = t.deadline + t.cost + x
return True
def bound_response_times(no_cpus, tasks, preemptive=True):
# DA's work applies to implicit-deadline tasks
assert forall(tasks)(lambda t: t.implicit_deadline())
x = task_tardiness_bound(no_cpus, tasks, preemptive)
if x is None:
return False
else:
for t in tasks:
t.response_time = t.deadline + t.cost + x
return True
def compute_response_details(no_cpus, tasks, rounds):
if (no_cpus == 1) and forall(tasks)(lambda t: t.prio_pt == t.period):
details = AnalysisDetails(tasks)
details.bounds = [task.period for task in tasks]
details.S_i = [0.0 for task in tasks]
details.G_i = [0.0 for task in tasks]
return details
if schedcat.sched.using_native:
native_ts = schedcat.sched.get_native_taskset(tasks)
gel_obj = native.GELPl(no_cpus, native_ts, rounds)
return AnalysisDetails(tasks, gel_obj)
else:
return compute_response_bounds(no_cpus, tasks, rounds)
def compute_response_details(no_cpus, tasks, rounds):
if (no_cpus == 1) and forall(tasks)(lambda t: t.pp == t.period):
details = AnalysisDetails(tasks)
details.bounds = [task.period for task in tasks]
details.S_i = [0.0 for task in tasks]
details.G_i = [0.0 for task in tasks]
return details
if schedcat.sched.using_native:
native_ts = schedcat.sched.get_native_taskset(tasks)
gel_obj = native.GELPl(no_cpus, native_ts, rounds)
return AnalysisDetails(tasks, gel_obj)
else:
return compute_response_bounds(no_cpus, tasks, rounds)
def is_schedulable_py(no_cpus,
tasks,
rta_min_step=1,
want_baruah=3000,
want_rta=True,
want_ffdbf=False,
want_load=False):
if tasks.utilization() > no_cpus or \
not forall(tasks)(lambda t: t.period >= t.cost):
# trivially infeasible
return False
else:
not_arbitrary = tasks.only_constrained_deadlines()
if no_cpus == 1 and tasks.density() <= 1:
# simply uniprocessor density condition
return True
elif no_cpus > 1:
# Baker's test can handle arbitrary deadlines.
if bak_test(no_cpus, tasks):
return True
# The other tests cannot.
if not_arbitrary:
# The density test is cheap, try it first.
if gfb_test(no_cpus, tasks):
return True
# Ok, try the slower ones.
if should_use_baruah_test(want_baruah, tasks, no_cpus) and \
bar_test(no_cpus, tasks):
return True
if want_rta and \
rta_test(no_cpus, tasks,
min_fixpoint_step=rta_min_step):
return True
# FF-DBF is almost always too slow.
if want_ffdbf and ffdbf_test(no_cpus, tasks):
return True
# If we get here, none of the tests passed.
return False
def is_schedulable(no_cpus, tasks):
return forall(tasks)(lambda t_k: task_schedulable(tasks, t_k, no_cpus))
def has_bounded_tardiness(no_cpus, tasks):
return tasks.utilization() <= no_cpus and forall(tasks)(lambda t: t.period >= t.cost)
def is_schedulable(num_cpus, tasks):
return forall(xrange(
len(tasks)))(lambda k: rta_schedulable_guan(k, tasks, num_cpus))
def has_bounded_tardiness(no_cpus, tasks):
return tasks.utilization() <= no_cpus and \
forall(tasks)(lambda t: t.period >= t.cost)
def only_constrained_deadlines(self):
return forall(self)(lambda t: t.constrained_deadline())
def only_implicit_deadlines(self):
return forall(self)(lambda t: t.implicit_deadline())
def has_bounded_tardiness(no_cpus, tasks):
"""Simple utilization bound: tasks.utilization() <= no_cpus.
This is also true for constrained-deadline tasks.
"""
return tasks.utilization() <= no_cpus and \
forall(tasks)(lambda t: t.period >= t.cost)
def is_schedulable(num_cpus, tasks, **kargs):
return forall(list(range(len(tasks))))(lambda k: rta_schedulable(k, tasks, num_cpus, **kargs))
def is_schedulable(no_cpus, tasks):
return forall(tasks)(lambda t_k: task_schedulable(tasks, t_k, no_cpus))
def has_bounded_tardiness(no_cpus, tasks):
"""Simple utilization bound: tasks.utilization() <= no_cpus.
This is also true for constrained-deadline tasks.
"""
return tasks.utilization() <= no_cpus and \
forall(tasks)(lambda t: t.period >= t.cost)
def is_schedulable(num_cpus, tasks):
return forall(xrange(len(tasks)))(lambda k: rta_schedulable_guan(k, tasks, num_cpus))
def only_constrained_deadlines(self):
return forall(self)(lambda t: t.constrained_deadline())
def only_implicit_deadlines(self):
return forall(self)(lambda t: t.implicit_deadline())