diff -r a625622cd8a1 -r aa3cff339427 src/python/m5/stats/__init__.py
--- a/src/python/m5/stats/__init__.py	Tue Jan 29 10:40:02 2013 +0000
+++ b/src/python/m5/stats/__init__.py	Tue Jan 29 10:45:40 2013 +0000
@@ -159,6 +159,7 @@
 
     d.sum = data.sum
     d.squares = data.squares
+    d.logs = data.logs
     d.samples = data.samples
 
     if isinstance(d, (Distribution, Histogram)):
diff -r a625622cd8a1 -r aa3cff339427 src/python/m5/stats/display.py
--- a/src/python/m5/stats/display.py	Tue Jan 29 10:40:02 2013 +0000
+++ b/src/python/m5/stats/display.py	Tue Jan 29 10:45:40 2013 +0000
@@ -296,6 +296,12 @@
         p.value = v.mean()
         p.display(out)
 
+        # Only the histogram calculates a geometric mean
+        if type(v) == Histogram:
+            p.name = "%s::gmean" % self.name
+            p.value = v.gmean()
+            p.display(out)
+
         p.name = "%s::stdev" % self.name
         p.value = v.stdev()
         p.display(out)
diff -r a625622cd8a1 -r aa3cff339427 src/python/m5/stats/info.py
--- a/src/python/m5/stats/info.py	Tue Jan 29 10:40:02 2013 +0000
+++ b/src/python/m5/stats/info.py	Tue Jan 29 10:45:40 2013 +0000
@@ -751,6 +751,7 @@
 class Histogram(Deviation):
     ## @brief Reset the Histogram. Call the super class's clear method.
     def clear(self):
+        self.logs = 0
         super(Histogram, self).clear()
 
     ## @brief Copy the histogram. Call the superclass copy method, then copy the
@@ -762,8 +763,19 @@
         copy.max = self.max
         copy.bucket_size = self.bucket_size
         copy.vector = self.vector[:]
+        copy.logs = self.logs
         return copy
 
+    ## @brief Calculate and return the geometric mean.
+    # @return The mean if the number of samples is greater than 0, float('nan')
+    # otherwise.
+    def gmean(self):
+        if self.samples == 0:
+            return float('nan')
+
+        import math
+        return math.exp(self.logs / self.samples)
+
     ## @brief Determine if it is possible to compare this histogram to another.
     # This is accomplished by checking that they are both of the same type, that
     # the min, max and bucket_size match and that the length of the vectors
diff -r a625622cd8a1 -r aa3cff339427 src/python/m5/stats/sql.py
--- a/src/python/m5/stats/sql.py	Tue Jan 29 10:40:02 2013 +0000
+++ b/src/python/m5/stats/sql.py	Tue Jan 29 10:45:40 2013 +0000
@@ -109,6 +109,7 @@
                        Column('sum', Float),
                        Column('squares', Float),
                        Column('samples', Float),
+                       Column('logs', Float),
                        Column('min', Float),
                        Column('max', Float),
                        Column('bucket', Float),
@@ -243,6 +244,7 @@
     sum = Column(Float)
     squares = Column(Float)
     samples = Column(Float)
+    logs = Column(Float)
     min = Column(Float)
     max = Column(Float)
     bucket = Column(Float)
@@ -258,10 +260,11 @@
 
 
     def __repr__(self):
-        return "<User('%d','%d','%f','%f','%f','%f','%f','%f','%s','%f','%f', \
-            '%f','%f')>" % (self.id, self.dump, self.sum, self.squares,
-            self.samples, self.min, self.max, self.bucket, self.vector,
-            self.min_val, self.max_val, self.underflow, self.overflow)
+        return "<User('%d','%d','%f','%f','%f','%f','%f','%f','%f','%s','%f', \
+            '%f','%f','%f')>" % (self.id, self.dump, self.sum, self.squares,
+            self.samples, self.logs, self.min, self.max, self.bucket,
+            self.vector, self.min_val, self.max_val, self.underflow,
+            self.overflow)
 
 # @brief Class used to insert sparse histograms into the database.
 class SparseHistValueClass(Base):
@@ -338,6 +341,9 @@
             a = array.array('f', data.vector)
             temp.vector = a.tostring()
 
+        if type(data) == Histogram:
+            temp.logs = data.logs
+
         if type(data) == Distribution:
             temp.min_val = data.min_val
             temp.max_val = data.max_val