ruby: modifies histogram add() function

This patch modifies the Histogram class' add() function so that it can add
linear histograms as well. The function assumes that the left end point of
the ranges of the two histograms are the same. It also assumes that when
the ranges of the two histogram are changed to accomodate an element not in
the range, the factor used in changing the range is same for both the
histograms.

This function is then used in removing one of the calls to the global
profiler*. The histograms for recording the delays incurred in processing
different requests are now maintained by the controllers. The profiler
adds these histograms when it needs to print the stats.

2 files changed, 84 insertions, 43 deletions

diff --git a/src/mem/ruby/common/Histogram.cc b/src/mem/ruby/common/Histogram.cc
index dcb723f1b..0558e5198 100644
--- a/src/mem/ruby/common/Histogram.cc
+++ b/src/mem/ruby/common/Histogram.cc
@@ -34,11 +34,10 @@
 
 using namespace std;
 
-Histogram::Histogram(int binsize, int bins)
+Histogram::Histogram(int binsize, uint32_t bins)
 {
     m_binsize = binsize;
-    m_bins = bins;
-    clear();
+    clear(bins);
 }
 
 Histogram::~Histogram()
@@ -46,29 +45,43 @@ Histogram::~Histogram()
 }
 
 void
-Histogram::clear(int binsize, int bins)
+Histogram::clear(int binsize, uint32_t bins)
 {
     m_binsize = binsize;
     clear(bins);
 }
 
 void
-Histogram::clear(int bins)
+Histogram::clear(uint32_t bins)
 {
-    m_bins = bins;
     m_largest_bin = 0;
     m_max = 0;
-    m_data.resize(m_bins);
-    for (int i = 0; i < m_bins; i++) {
+    m_data.resize(bins);
+    for (uint32_t i = 0; i < bins; i++) {
         m_data[i] = 0;
     }
+
     m_count = 0;
     m_max = 0;
-
     m_sumSamples = 0;
     m_sumSquaredSamples = 0;
 }
 
+void
+Histogram::doubleBinSize()
+{
+    assert(m_binsize != -1);
+    uint32_t t_bins = m_data.size();
+
+    for (uint32_t i = 0; i < t_bins/2; i++) {
+        m_data[i] = m_data[i*2] + m_data[i*2 + 1];
+    }
+    for (uint32_t i = t_bins/2; i < t_bins; i++) {
+        m_data[i] = 0;
+    }
+
+    m_binsize *= 2;
+}
 
 void
 Histogram::add(int64 value)
@@ -80,7 +93,8 @@ Histogram::add(int64 value)
     m_sumSamples += value;
     m_sumSquaredSamples += (value*value);
 
-    int index;
+    uint32_t index;
+
     if (m_binsize == -1) {
         // This is a log base 2 histogram
         if (value == 0) {
@@ -93,37 +107,59 @@ Histogram::add(int64 value)
         }
     } else {
         // This is a linear histogram
-        while (m_max >= (m_bins * m_binsize)) {
-            for (int i = 0; i < m_bins/2; i++) {
-                m_data[i] = m_data[i*2] + m_data[i*2 + 1];
-            }
-            for (int i = m_bins/2; i < m_bins; i++) {
-                m_data[i] = 0;
-            }
-            m_binsize *= 2;
-        }
+        uint32_t t_bins = m_data.size();
+
+        while (m_max >= (t_bins * m_binsize)) doubleBinSize();
         index = value/m_binsize;
     }
-    assert(index >= 0);
+
+    assert(index < m_data.size());
     m_data[index]++;
     m_largest_bin = max(m_largest_bin, index);
 }
 
 void
-Histogram::add(const Histogram& hist)
+Histogram::add(Histogram& hist)
 {
-    assert(hist.getBins() == m_bins);
-    assert(hist.getBinSize() == -1);  // assume log histogram
-    assert(m_binsize == -1);
+    uint32_t t_bins = m_data.size();
 
-    for (int j = 0; j < hist.getData(0); j++) {
-        add(0);
+    if (hist.getBins() != t_bins) {
+        fatal("Histograms with different number of bins cannot be combined!");
     }
 
-    for (int i = 1; i < m_bins; i++) {
-        for (int j = 0; j < hist.getData(i); j++) {
-            add(1<<(i-1));  // account for the + 1 index
+    m_max = max(m_max, hist.getMax());
+    m_count += hist.size();
+    m_sumSamples += hist.getTotal();
+    m_sumSquaredSamples += hist.getSquaredTotal();
+
+    // Both histograms are log base 2.
+    if (hist.getBinSize() == -1 && m_binsize == -1) {
+        for (int j = 0; j < hist.getData(0); j++) {
+            add(0);
+        }
+
+        for (uint32_t i = 1; i < t_bins; i++) {
+            for (int j = 0; j < hist.getData(i); j++) {
+                add(1<<(i-1));  // account for the + 1 index
+            }
+        }
+    } else if (hist.getBinSize() >= 1 && m_binsize >= 1) {
+        // Both the histogram are linear.
+        // We are assuming that the two histograms have the same
+        // minimum value that they can store.
+
+        while (m_binsize > hist.getBinSize()) hist.doubleBinSize();
+        while (hist.getBinSize() > m_binsize) doubleBinSize();
+
+        assert(m_binsize == hist.getBinSize());
+
+        for (uint32_t i = 0; i < t_bins; i++) {
+            m_data[i] += hist.getData(i);
+
+            if (m_data[i] > 0) m_largest_bin = i;
         }
+    } else {
+        fatal("Don't know how to combine log and linear histograms!");
     }
 }
 
@@ -177,7 +213,8 @@ Histogram::printWithMultiplier(ostream& out, double multiplier) const
             << " | ";
         out << "standard deviation: " << getStandardDeviation() << " |";
     }
-    for (int i = 0; i < m_bins && i <= m_largest_bin; i++) {
+
+    for (uint32_t i = 0; i <= m_largest_bin; i++) {
         if (multiplier == 1.0) {
             out << " " << m_data[i];
         } else {
diff --git a/src/mem/ruby/common/Histogram.hh b/src/mem/ruby/common/Histogram.hh
index bfc0e4293..c34e39af1 100644
--- a/src/mem/ruby/common/Histogram.hh
+++ b/src/mem/ruby/common/Histogram.hh
@@ -37,34 +37,38 @@
 class Histogram
 {
   public:
-    Histogram(int binsize = 1, int bins = 50);
+    Histogram(int binsize = 1, uint32_t bins = 50);
     ~Histogram();
 
     void add(int64 value);
-    void add(const Histogram& hist);
-    void clear() { clear(m_bins); }
-    void clear(int bins);
-    void clear(int binsize, int bins);
-    int64 size() const { return m_count; }
-    int getBins() const { return m_bins; }
+    void add(Histogram& hist);
+    void doubleBinSize();
+
+    void clear() { clear(m_data.size()); }
+    void clear(uint32_t bins);
+    void clear(int binsize, uint32_t bins);
+
+    uint64_t size() const { return m_count; }
+    uint32_t getBins() const { return m_data.size(); }
     int getBinSize() const { return m_binsize; }
     int64 getTotal() const { return m_sumSamples; }
-    int64 getData(int index) const { return m_data[index]; }
+    uint64_t getSquaredTotal() const { return m_sumSquaredSamples; }
+    uint64_t getData(int index) const { return m_data[index]; }
+    int64 getMax() const { return m_max; }
 
     void printWithMultiplier(std::ostream& out, double multiplier) const;
     void printPercent(std::ostream& out) const;
     void print(std::ostream& out) const;
 
 private:
-    std::vector<int64> m_data;
+    std::vector<uint64_t> m_data;
     int64 m_max;          // the maximum value seen so far
-    int64 m_count;                // the number of elements added
+    uint64_t m_count;                // the number of elements added
     int m_binsize;                // the size of each bucket
-    int m_bins;           // the number of buckets
-    int m_largest_bin;      // the largest bin used
+    uint32_t m_largest_bin;      // the largest bin used
 
     int64 m_sumSamples;   // the sum of all samples
-    int64 m_sumSquaredSamples; // the sum of the square of all samples
+    uint64_t m_sumSquaredSamples; // the sum of the square of all samples
 
     double getStandardDeviation() const;
 };