diff --git a/idi/util/__init__.py b/idi/util/__init__.py
index e238afb..0787f5b 100644
--- a/idi/util/__init__.py
+++ b/idi/util/__init__.py
@@ -11,6 +11,7 @@
 import itertools as _it
 from functools import lru_cache
 
+
 def radial_profile(data, center=None, calcStd=False, os=1):
     """
     calculates a ND radial profile of data around center. will ignore nans
@@ -212,7 +213,9 @@ def atleastnd(array, n):
         array = _np.array(array)
     return array[tuple((n - array.ndim) * [None] + [...])]
 
-@lru_cache
+
+@args2tuple
+@lru_cache(maxsize=None)
 def fastlen(x, factors=(2, 3, 5, 7, 11)):
     """
     return N>=x conisting only of the prime factors given as factors
diff --git a/idi/util/funchelper.py b/idi/util/funchelper.py
index 8e07613..5b4beb6 100644
--- a/idi/util/funchelper.py
+++ b/idi/util/funchelper.py
@@ -44,10 +44,12 @@ def asgen_helper(arg, *args, **kw):
 def parallel(fn=None):
     from collections import deque
     import time
+
     try:
         from pathos.multiprocessing import Pool
     except ImportError:
         import warnings
+
         warnings.warn('no pathos available, be careful with parallel decorator and pickling errors.')
         from multiprocessing import Pool
 
@@ -78,3 +80,16 @@ def chain(*fns):
 
 def group(iterable, n):
     return zip(*([iter(iterable)] * n))
+
+
+def args2tuple(function):
+    import numpy
+
+    def wrapper(*args, **kwargs):
+        args = [tuple(x) if type(x) == list else x for x in args]
+        kwargs = {k: tuple(x) if type(x) == list else x for k, x in kwargs.items()}
+        args = [tuple(x.ravel()) if type(x) == numpy.ndarray else x for x in args]
+        kwargs = {k: tuple(x.ravel()) if type(x) == numpy.ndarray else x for k, x in kwargs.items()}
+        return function(*args, **kwargs)
+
+    return wrapper