Randomize the order of selecting CPUs when we try to dispatch benchmarks onto workers.

This avoids a bias towards the lower-numbered CPUs.

PiperOrigin-RevId: 803187095
Change-Id: I829b956b86dc8d8498d62cdbe2fc60c3ce8bf9db

Author: rjogrady

fleetbench/parallel/parallel_bench_lib.py

@@ -353,8 +353,13 @@ def _RunSchedulingLoop(self) -> None:
 
       self.utilization_samples.append((pd.Timestamp.now(), total_utilization))
 
+      # Avoid biasing towards lower-numbered CPUs by randomizing the order here.
+      # That way CPUs with the same utilization will be randomly selected.
+      cpu_util_items = list(utilization_per_cpu.items())
+      np.random.shuffle(cpu_util_items)
+
       least_busy_cpus = collections.OrderedDict(
-          sorted(utilization_per_cpu.items(), key=lambda item: item[1])
+          sorted(cpu_util_items, key=lambda item: item[1])
       )
 
       # E.g. we are at 50% utilization, target is 70%.