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Diffstat (limited to 'src/mem/ruby/common/Histogram.cc')
| -rw-r--r-- | src/mem/ruby/common/Histogram.cc | 185 |
1 files changed, 185 insertions, 0 deletions
diff --git a/src/mem/ruby/common/Histogram.cc b/src/mem/ruby/common/Histogram.cc new file mode 100644 index 000000000..7f9a7027e --- /dev/null +++ b/src/mem/ruby/common/Histogram.cc @@ -0,0 +1,185 @@ + +/* + * Copyright (c) 1999-2008 Mark D. Hill and David A. Wood + * All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions are + * met: redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer; + * redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution; + * neither the name of the copyright holders nor the names of its + * contributors may be used to endorse or promote products derived from + * this software without specific prior written permission. + * + * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + */ + +/* + * $Id$ + * + */ + +#include "mem/ruby/common/Histogram.hh" + +Histogram::Histogram(int binsize, int bins) +{ + m_binsize = binsize; + m_bins = bins; + clear(); +} + +Histogram::~Histogram() +{ +} + +void Histogram::clear(int binsize, int bins) +{ + m_binsize = binsize; + clear(bins); +} + +void Histogram::clear(int bins) +{ + m_bins = bins; + m_largest_bin = 0; + m_max = 0; + m_data.setSize(m_bins); + for (int i = 0; i < m_bins; i++) { + m_data[i] = 0; + } + m_count = 0; + m_max = 0; + + m_sumSamples = 0; + m_sumSquaredSamples = 0; +} + + +void Histogram::add(int64 value) +{ + assert(value >= 0); + m_max = max(m_max, value); + m_count++; + + m_sumSamples += value; + m_sumSquaredSamples += (value*value); + + int index; + if (m_binsize == -1) { + // This is a log base 2 histogram + if (value == 0) { + index = 0; + } else { + index = int(log(double(value))/log(2.0))+1; + if (index >= m_data.size()) { + index = m_data.size()-1; + } + } + } 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; + } + index = value/m_binsize; + } + assert(index >= 0); + m_data[index]++; + m_largest_bin = max(m_largest_bin, index); +} + +void Histogram::add(const Histogram& hist) +{ + assert(hist.getBins() == m_bins); + assert(hist.getBinSize() == -1); // assume log histogram + assert(m_binsize == -1); + + for (int j = 0; j < hist.getData(0); j++) { + add(0); + } + + 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 + } + } + +} + +// Computation of standard deviation of samples a1, a2, ... aN +// variance = [SUM {ai^2} - (SUM {ai})^2/N]/(N-1) +// std deviation equals square root of variance +double Histogram::getStandardDeviation() const +{ + double variance; + if(m_count > 1){ + variance = (double)(m_sumSquaredSamples - m_sumSamples*m_sumSamples/m_count)/(m_count - 1); + } else { + return 0; + } + return sqrt(variance); +} + +void Histogram::print(ostream& out) const +{ + printWithMultiplier(out, 1.0); +} + +void Histogram::printPercent(ostream& out) const +{ + if (m_count == 0) { + printWithMultiplier(out, 0.0); + } else { + printWithMultiplier(out, 100.0/double(m_count)); + } +} + +void Histogram::printWithMultiplier(ostream& out, double multiplier) const +{ + if (m_binsize == -1) { + out << "[binsize: log2 "; + } else { + out << "[binsize: " << m_binsize << " "; + } + out << "max: " << m_max << " "; + out << "count: " << m_count << " "; + // out << "total: " << m_sumSamples << " "; + if (m_count == 0) { + out << "average: NaN |"; + out << "standard deviation: NaN |"; + } else { + out << "average: " << setw(5) << ((double) m_sumSamples)/m_count << " | "; + out << "standard deviation: " << getStandardDeviation() << " |"; + } + for (int i = 0; i < m_bins && i <= m_largest_bin; i++) { + if (multiplier == 1.0) { + out << " " << m_data[i]; + } else { + out << " " << double(m_data[i]) * multiplier; + } + } + out << " ]"; +} + +bool node_less_then_eq(const Histogram* n1, const Histogram* n2) +{ + return (n1->size() > n2->size()); +} |