diff --git a/deepwalk/__main__.py b/deepwalk/__main__.py
index 00f7bc33aea28a69156ddc48fb085b384c8df29f..c331aef8cb5255e3cd884c0606a0dceb95505d03 100644
--- a/deepwalk/__main__.py
+++ b/deepwalk/__main__.py
@@ -1,6 +1,7 @@
 #! /usr/bin/env python
 # -*- coding: utf-8 -*-
 
+import os
 import sys
 import random
 from io import open
@@ -16,6 +17,13 @@ from skipgram import Skipgram
 
 from six import text_type as unicode
 from six import iteritems
+from six.moves import range
+
+import psutil
+from multiprocessing import cpu_count
+
+p = psutil.Process(os.getpid())
+p.set_cpu_affinity(list(range(cpu_count())))
 
 logger = logging.getLogger(__name__)
 LOGFORMAT = "%(asctime).19s %(levelname)s %(filename)s: %(lineno)s %(message)s"
@@ -68,11 +76,15 @@ def process(args):
                                          path_length=args.walk_length, alpha=0, rand=random.Random(args.seed),
                                          num_workers=args.workers)
 
-    # use degree distribution for frequency in tree
-    vertex_frequency = G.degree(nodes=G.iterkeys())
+    print("Counting vertex frequency...")
+    if not args.vertex_freq_degree:
+      vertex_counts = serialized_walks.count_textfiles(walk_files, args.workers)
+    else:
+      # use degree distribution for frequency in tree
+      vertex_counts = G.degree(nodes=G.iterkeys())
 
     print("Training...")
-    model = Skipgram(sentences=serialized_walks.combine_files_iter(walk_files), vocabulary_counts=vertex_frequency,
+    model = Skipgram(sentences=serialized_walks.combine_files_iter(walk_files), vocabulary_counts=vertex_counts,
                      size=args.representation_size,
                      window=args.window_size, min_count=0, workers=args.workers)
 
@@ -117,6 +129,11 @@ def main():
   parser.add_argument('--undirected', default=True, type=bool,
                       help='Treat graph as undirected.')
 
+  parser.add_argument('--vertex-freq-degree', default=False, action='store_true',
+                      help='Use vertex degree to estimate the frequency of nodes '
+                           'in the random walks. This option is faster than '
+                           'calculating the vocabulary.')
+
   parser.add_argument('--walk-length', default=40, type=int,
                       help='Length of the random walk started at each node')
 
diff --git a/deepwalk/walks.py b/deepwalk/walks.py
index eaa29540b4a296944637f5a187d1ca21da891623..58d497f4a2528f0fb336ead276e2d150053845a6 100644
--- a/deepwalk/walks.py
+++ b/deepwalk/walks.py
@@ -2,10 +2,12 @@ import logging
 from io import open
 from os import path
 from time import time
-from itertools import izip
 from multiprocessing import cpu_count
 import random
 from concurrent.futures import ProcessPoolExecutor
+from collections import Counter
+
+from six.moves import zip
 
 from deepwalk import graph
 
@@ -16,6 +18,29 @@ __current_graph = None
 # speed up the string encoding
 __vertex2str = None
 
+def count_words(file):
+  """ Counts the word frequences in a list of sentences.
+
+  Note:
+    This is a helper function for parallel execution of `Vocabulary.from_text`
+    method.
+  """
+  c = Counter()
+  with open(file, 'r') as f:
+    for l in f:
+      words = l.strip().split()
+      c.update(words)
+  return c
+
+
+def count_textfiles(files, workers=1):
+  c = Counter()
+  with ProcessPoolExecutor(max_workers=workers) as executor:
+    for c_ in executor.map(count_words, files):
+      c.update(c_)
+  return c
+
+
 def count_lines(f):
   if path.isfile(f):
     num_lines = sum(1 for line in open(f))
@@ -52,7 +77,7 @@ def write_walks_to_disk(G, filebase, num_paths, path_length, alpha=0, rand=rando
                         for x in graph.grouper(int(num_paths / num_workers)+1, range(1, num_paths+1))]
 
   with ProcessPoolExecutor(max_workers=num_workers) as executor:
-    for size, file_, ppw in izip(executor.map(count_lines, files_list), files_list, paths_per_worker):
+    for size, file_, ppw in zip(executor.map(count_lines, files_list), files_list, paths_per_worker):
       if always_rebuild or size != (ppw*expected_size):
         args_list.append((ppw, path_length, alpha, random.Random(rand.randint(0, 2**31)), file_))
       else:
@@ -68,4 +93,4 @@ def combine_files_iter(file_list):
   for file in file_list:
     with open(file, 'r') as f:
       for line in f:
-        yield line.split()
\ No newline at end of file
+        yield line.split()
diff --git a/requirements.txt b/requirements.txt
index b607e1d2f4736ab85c9e05f4c52e6acbeb761af2..3138a4d8a8adf2fb9aee42d64db10f1ea0ae3f6e 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,3 +5,4 @@ futures>=2.1.6
 six>=1.7.3
 gensim>=0.10.0
 scipy>=0.7.0
+psutil>=2.1.1