diff --git a/doc/source/release.rst b/doc/source/release.rst
index 2583b47d9b3bf..6f9aa1c01fc37 100644
--- a/doc/source/release.rst
+++ b/doc/source/release.rst
@@ -159,6 +159,8 @@ Improvements to existing features
 - ``StataWriter`` and ``DataFrame.to_stata`` accept time stamp and data labels (:issue:`6545`)
 - offset/freq info now in Timestamp __repr__ (:issue:`4553`)
 - Support passing ``encoding`` with xlwt (:issue:`3710`)
+- Performance improvement when converting ``DatetimeIndex`` to floating ordinals 
+  using ``DatetimeConverter`` (:issue:`6636`)
 
 .. _release.bug_fixes-0.14.0:
 
diff --git a/pandas/tseries/converter.py b/pandas/tseries/converter.py
index d059d229ef22e..b9939976fded8 100644
--- a/pandas/tseries/converter.py
+++ b/pandas/tseries/converter.py
@@ -16,6 +16,7 @@
 import pandas.core.common as com
 from pandas.core.index import Index
 
+from pandas.core.series import Series
 from pandas.tseries.index import date_range
 import pandas.tseries.tools as tools
 import pandas.tseries.frequencies as frequencies
@@ -144,7 +145,10 @@ def _dt_to_float_ordinal(dt):
     preserving hours, minutes, seconds and microseconds.  Return value
     is a :func:`float`.
     """
-    base = dates.date2num(dt)
+    if isinstance(dt, (np.ndarray, Series)) and com.is_datetime64_ns_dtype(dt):
+        base = dates.epoch2num(dt.asi8 / 1.0E9)
+    else:
+        base = dates.date2num(dt)
     return base
 
 
diff --git a/pandas/tseries/tests/test_converter.py b/pandas/tseries/tests/test_converter.py
index 29137f9cb3e50..902b9cb549e32 100644
--- a/pandas/tseries/tests/test_converter.py
+++ b/pandas/tseries/tests/test_converter.py
@@ -5,8 +5,11 @@
 import nose
 
 import numpy as np
+from numpy.testing import assert_almost_equal as np_assert_almost_equal
+from pandas import Timestamp
 from pandas.compat import u
 import pandas.util.testing as tm
+from pandas.tseries.offsets import Second, Milli, Micro
 
 try:
     import pandas.tseries.converter as converter
@@ -46,9 +49,48 @@ def test_conversion(self):
         rs = self.dtc.convert('2012-1-1', None, None)
         self.assertEqual(rs, xp)
 
+        rs = self.dtc.convert(Timestamp('2012-1-1'), None, None)
+        self.assertEqual(rs, xp)
+
+    def test_conversion_float(self):
+        decimals = 9
+
+        rs = self.dtc.convert(Timestamp('2012-1-1 01:02:03', tz='UTC'), None, None)
+        xp = converter.dates.date2num(Timestamp('2012-1-1 01:02:03', tz='UTC'))
+        np_assert_almost_equal(rs, xp, decimals)
+
+        rs = self.dtc.convert(Timestamp('2012-1-1 09:02:03', tz='Asia/Hong_Kong'), None, None)
+        np_assert_almost_equal(rs, xp, decimals)
+
+        rs = self.dtc.convert(datetime(2012, 1, 1, 1, 2, 3), None, None)
+        np_assert_almost_equal(rs, xp, decimals)
+
     def test_time_formatter(self):
         self.tc(90000)
 
+    def test_dateindex_conversion(self):
+        decimals = 9
+
+        for freq in ('B', 'L', 'S'):
+            dateindex = tm.makeDateIndex(k = 10, freq = freq)
+            rs = self.dtc.convert(dateindex, None, None)
+            xp = converter.dates.date2num(dateindex)
+            np_assert_almost_equal(rs, xp, decimals)
+
+    def test_resolution(self):
+        def _assert_less(ts1, ts2):
+            val1 = self.dtc.convert(ts1, None, None)
+            val2 = self.dtc.convert(ts2, None, None)
+            if not val1 < val2:
+                raise AssertionError('{0} is not less than {1}.'.format(val1, val2))
+
+        # Matplotlib's time representation using floats cannot distinguish intervals smaller 
+        # than ~10 microsecond in the common range of years. 
+        ts = Timestamp('2012-1-1')
+        _assert_less(ts, ts + Second())
+        _assert_less(ts, ts + Milli())
+        _assert_less(ts, ts + Micro(50))
+
 
 if __name__ == '__main__':
     import nose
diff --git a/vb_suite/timeseries.py b/vb_suite/timeseries.py
index c43d2fb76dbdb..93821c3be3c2c 100644
--- a/vb_suite/timeseries.py
+++ b/vb_suite/timeseries.py
@@ -269,3 +269,15 @@ def date_range(start=None, end=None, periods=None, freq=None):
 dataframe_resample_max_numpy = \
     Benchmark("df.resample('1s', how=np.max)", setup)
 
+
+#----------------------------------------------------------------------
+# DatetimeConverter
+
+setup = common_setup + """
+from pandas.tseries.converter import DatetimeConverter
+"""
+
+datetimeindex_converter = \
+    Benchmark('DatetimeConverter.convert(rng, None, None)', 
+              setup, start_date=datetime(2013, 1, 1))
+