diff --git a/bin/bank/pycbc_brute_bank b/bin/bank/pycbc_brute_bank
index 58cfcc9ff19..0fd9709cd4e 100644
--- a/bin/bank/pycbc_brute_bank
+++ b/bin/bank/pycbc_brute_bank
@@ -26,6 +26,7 @@ import argparse
 import pickle
 import numpy.random
 from scipy.stats import gaussian_kde
+import multiprocessing
 
 import pycbc.waveform, pycbc.filter, pycbc.types, pycbc.psd, pycbc.fft, pycbc.conversions
 from pycbc import transforms
@@ -75,6 +76,7 @@ parser.add_argument('--tau0-crawl', type=float)
 parser.add_argument('--tau0-start', type=float)
 parser.add_argument('--tau0-end', type=float)
 parser.add_argument('--tau0-cutoff-frequency', type=float, default=15.0)
+parser.add_argument('--num_cores', type=int, default=1, help='number of cores for parallelization.')
 pycbc.psd.insert_psd_option_group(parser)
 args = parser.parse_args()
 
@@ -247,20 +249,52 @@ class TriangleBank(object):
     def check_params(self, gen, params, threshold):
         num_tried = 0
         num_added = 0
-        for i in range(len(tuple(params.values())[0])):
-            num_tried += 1.0
-
-            try:
-                hp = gen.generate(**{key:params[key][i] for key in params})
-            except Exception as err:
-                print(err)
-                continue
-
-            hp.gen = gen
-            hp.threshold = threshold
-            if hp not in self:
-                num_added += 1
-                self.insert(hp)
+        total_num = len(tuple(params.values())[0])
+
+        if args.num_cores == 1:
+            for i in range(total_num):
+                num_tried += 1.0
+
+                try:
+                    hp = gen.generate(**{key:params[key][i] for key in params})
+                except Exception as err:
+                    print(err)
+                    continue
+
+                hp.gen = gen
+                hp.threshold = threshold
+                if hp not in self:
+                    num_added += 1
+                    self.insert(hp)
+
+        # use multiprocessing
+        elif args.num_cores > 1:
+            waveform_cache = []
+            with multiprocessing.Pool(args.num_cores) as pool:
+                for return_wf in pool.imap_unordered(
+                    wf_wrapper, 
+                    ({k: params[k][idx] for k in params} for idx in range(total_num))
+                ):
+                    waveform_cache += [return_wf]
+            
+            for i in range(total_num):
+                num_tried += 1
+                hp = waveform_cache[i]
+
+                if isinstance(hp, pycbc.types.FrequencySeries):
+                    hp.gen = gen
+                    hp.threshold = threshold 
+                    if hp not in self:
+                        num_added += 1
+                        self.insert(hp)
+                elif numpy.isnan(hp):
+                    logging.info("Waveform generation failed!")
+                    continue
+                else:
+                    raise ValueError("Waveform generation problem.")
+        
+        else:
+            raise ValueError("Number of cores should be a positive integer.")
 
         return bank, num_added / float(num_tried)
 
@@ -337,6 +371,14 @@ gen = GenUniformWaveform(args.buffer_length,
     args.sample_rate, args.low_frequency_cutoff)
 bank = TriangleBank()
 
+if args.num_cores > 1:
+    def wf_wrapper(p):
+        try:
+            hp = gen.generate(**p)
+            return hp
+        except Exception:
+            return numpy.nan
+
 if args.input_file:
     f = h5py.File(args.input_file, 'r')
     params = {k: f[k][:] for k in f}