def apply_lp_dflp_bounds(all_tasks, resource_mapping): model = get_cpp_model(all_tasks) topo = get_cpp_topology(resource_mapping) res = lp_cpp.lp_dflp_bounds(model, topo) for i, t in enumerate(all_tasks): t.suspended = res.get_remote_blocking(i) t.blocked = res.get_blocking_term(i) return res
def apply_lp_dflp_bounds(all_tasks, resource_mapping, use_py=False): if use_py or not lp_cpp_available: apply_py_lp_bounds(dflp, all_tasks, resource_mapping) else: model = get_cpp_model(all_tasks) topo = get_cpp_topology(resource_mapping) res = lp_cpp.lp_dflp_bounds(model, topo) for i, t in enumerate(all_tasks): t.suspended = res.get_remote_blocking(i) t.blocked = res.get_blocking_term(i) return res