Fix a couple more bugs which was causing significant slowdown b/c of incorrect scheduling

            raise TypeError(f"Invalid type for utilization: {type(trace)}.")

    def run_simulation(self, jobs, timesteps):

        """ Generator that yields after each simulation tick """

        last_submit_time = 0

    def run_simulation(self, jobs, timesteps, autoshutdown=False):

        """Generator that yields after each simulation tick."""

        self.timesteps = timesteps

        for job_info in jobs:

            job = Job(job_info, self.current_time)

            self.add_job(job)

        # Sort pending jobs by submit_time.

        jobs_to_submit = sorted(jobs, key=lambda j: j['submit_time'])

        for timestep in range(timesteps):

            # Submit jobs whose submit_time is <= current_time

            while jobs_to_submit and jobs_to_submit[0]['submit_time'] <= self.current_time:

                job_info = jobs_to_submit.pop(0)

                job = Job(job_info, self.current_time)

                self.add_job(job)

            # Schedule jobs that are now in the queue.

            self.scheduler.schedule(self.queue, self.running, self.current_time)

            # Stop the simulation if no more jobs are running or in the queue

            if not self.queue and not self.running and not self.replay:

            # Stop the simulation if no more jobs are running or in the queue.

            if autoshutdown and not self.queue and not self.running and not self.replay:

                print(f"[DEBUG] {self.config['system_name']} - Stopping simulation at time {self.current_time}")

                break

            if self.debug and timestep % self.config['UI_UPDATE_FREQ'] == 0:

                print(".", end="", flush=True)

            yield self.tick()

    def get_stats(self):

        """ Return output statistics """

        sum_values = lambda values: sum(x[1] for x in values) if values else 0

        # Iterate over a copy of the queue since we might remove items

        for job in queue[:]:

            # Check if the resource manager has enough nodes.

            if len(self.resource_manager.available_nodes) >= job.nodes_required:

                # Use ResourceManager to assign nodes.

            # For synthetic jobs the number of requested nodes is given.

            # Make sure the available nodes count meets job.nodes_required.

            synthetic_bool = len(self.resource_manager.available_nodes) >= job.nodes_required

            # For telemetry replay jobs a list of requested nodes is provided.

            # Make sure the requested nodes are available.

            telemetry_bool = False

            if job.requested_nodes:

                telemetry_bool = set(job.requested_nodes).issubset(set(self.resource_manager.available_nodes))

            if synthetic_bool or telemetry_bool:

                self.resource_manager.assign_nodes_to_job(job, current_time)

                running.append(job)

                queue.remove(job)