diff --git a/src/share/vm/gc_implementation/shared/gcUtil.cpp b/src/share/vm/gc_implementation/shared/gcUtil.cpp
index 5325fee218b0e42f2bee9fa205fa740a0d886542..3b9fd7a68aa8fd49f9f93d28982af63b4b6d8771 100644
--- a/src/share/vm/gc_implementation/shared/gcUtil.cpp
+++ b/src/share/vm/gc_implementation/shared/gcUtil.cpp
@@ -31,9 +31,15 @@ float AdaptiveWeightedAverage::compute_adaptive_average(float new_sample,
                                                         float average) {
   // We smooth the samples by not using weight() directly until we've
   // had enough data to make it meaningful. We'd like the first weight
-  // used to be 1, the second to be 1/2, etc until we have 100/weight
-  // samples.
-  unsigned count_weight = 100/count();
+  // used to be 1, the second to be 1/2, etc until we have
+  // OLD_THRESHOLD/weight samples.
+  unsigned count_weight = 0;
+
+  // Avoid division by zero if the counter wraps (7158457)
+  if (!is_old()) {
+    count_weight = OLD_THRESHOLD/count();
+  }
+
   unsigned adaptive_weight = (MAX2(weight(), count_weight));
 
   float new_avg = exp_avg(average, new_sample, adaptive_weight);
@@ -43,8 +49,6 @@ float AdaptiveWeightedAverage::compute_adaptive_average(float new_sample,
 
 void AdaptiveWeightedAverage::sample(float new_sample) {
   increment_count();
-  assert(count() != 0,
-         "Wraparound -- history would be incorrectly discarded");
 
   // Compute the new weighted average
   float new_avg = compute_adaptive_average(new_sample, average());
diff --git a/src/share/vm/gc_implementation/shared/gcUtil.hpp b/src/share/vm/gc_implementation/shared/gcUtil.hpp
index 8dd3258de0a89d8d5f9ccd3ac88056f69509bb99..86daba64c3f6383f7cb522c0e9479a85a871e3dc 100644
--- a/src/share/vm/gc_implementation/shared/gcUtil.hpp
+++ b/src/share/vm/gc_implementation/shared/gcUtil.hpp
@@ -50,11 +50,20 @@ class AdaptiveWeightedAverage : public CHeapObj {
   unsigned         _weight;         // The weight used to smooth the averages
                                     //   A higher weight favors the most
                                     //   recent data.
+  bool             _is_old;         // Has enough historical data
+
+  const static unsigned OLD_THRESHOLD = 100;
 
  protected:
   float            _last_sample;    // The last value sampled.
 
-  void  increment_count()       { _sample_count++;       }
+  void  increment_count() {
+    _sample_count++;
+    if (!_is_old && _sample_count > OLD_THRESHOLD) {
+      _is_old = true;
+    }
+  }
+
   void  set_average(float avg)  { _average = avg;        }
 
   // Helper function, computes an adaptive weighted average
@@ -64,13 +73,15 @@ class AdaptiveWeightedAverage : public CHeapObj {
  public:
   // Input weight must be between 0 and 100
   AdaptiveWeightedAverage(unsigned weight, float avg = 0.0) :
-    _average(avg), _sample_count(0), _weight(weight), _last_sample(0.0) {
+    _average(avg), _sample_count(0), _weight(weight), _last_sample(0.0),
+    _is_old(false) {
   }
 
   void clear() {
     _average = 0;
     _sample_count = 0;
     _last_sample = 0;
+    _is_old = false;
   }
 
   // Useful for modifying static structures after startup.
@@ -84,7 +95,8 @@ class AdaptiveWeightedAverage : public CHeapObj {
   float    average() const       { return _average;       }
   unsigned weight()  const       { return _weight;        }
   unsigned count()   const       { return _sample_count;  }
-  float    last_sample() const   { return _last_sample; }
+  float    last_sample() const   { return _last_sample;   }
+  bool     is_old()  const       { return _is_old;        }
 
   // Update data with a new sample.
   void sample(float new_sample);