Switched to Pooling and local aggregation

lib/utils/parallel.py

@@ -2,10 +2,12 @@ import multiprocessing as mp
 import time
 
 
-def run_n_in_parallel(f, n, **kwargs):
+def run_n_in_parallel(f, n, processes=0, **kwargs):
+    processes = processes if processes else mp.cpu_count()
     output = mp.Queue()
     kwargs.update(output=output)
     # Setup a list of processes that we want to run
+
     processes = [mp.Process(target=f, kwargs=kwargs) for _ in range(n)]
     # Run processes
     results = []