def apply_lp_part_fmlp_bounds(all_tasks):
# LP-based analysis of the partitioned, preemptive FMLP+
model = get_cpp_model(all_tasks)
res = lp_cpp.lp_part_fmlp_bounds(model)
for i,t in enumerate(all_tasks):
# remote blocking <=> self-suspension time
t.suspended = res.get_remote_blocking(i)
# all blocking, including local blocking
t.blocked = res.get_blocking_term(i)
t.locally_blocked = res.get_local_blocking(i)
return res
def apply_lp_part_fmlp_bounds(all_tasks):
# LP-based analysis of the partitioned, preemptive FMLP+
model = get_cpp_model(all_tasks)
res = lp_cpp.lp_part_fmlp_bounds(model)
for i, t in enumerate(all_tasks):
# remote blocking <=> self-suspension time
t.suspended = res.get_remote_blocking(i)
# all blocking, including local blocking
t.blocked = res.get_blocking_term(i)
t.locally_blocked = res.get_local_blocking(i)
return res