276 lines
8.2 KiB
C++
276 lines
8.2 KiB
C++
/*
|
|
* Copyright (c) 2003-2005 The Regents of The University of Michigan
|
|
* 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.
|
|
*
|
|
* Authors: Steve Reinhardt
|
|
* Lisa Hsu
|
|
*/
|
|
|
|
#include <string>
|
|
#include <sstream>
|
|
|
|
#include "base/hybrid_pred.hh"
|
|
#include "base/statistics.hh"
|
|
#include "sim/stats.hh"
|
|
|
|
using namespace std;
|
|
|
|
HybridPredictor::HybridPredictor(const char *_p_name, const char *_z_name,
|
|
const char *_o_name,
|
|
unsigned _index_bits, unsigned _counter_bits,
|
|
unsigned _zero_change, unsigned _one_change,
|
|
unsigned _thresh,
|
|
unsigned _global_bits,
|
|
unsigned _global_thresh,
|
|
bool _reg_individual_stats)
|
|
{
|
|
stringstream local_name, global_name;
|
|
|
|
pred_name = _p_name;
|
|
one_name = _o_name;
|
|
zero_name = _z_name;
|
|
reg_individual_stats = _reg_individual_stats;
|
|
|
|
local_name << pred_name.c_str() << ":L";
|
|
local = new SaturatingCounterPred(local_name.str(), zero_name, one_name,
|
|
_index_bits, _counter_bits,
|
|
_zero_change, _one_change, _thresh);
|
|
|
|
global_name << pred_name.c_str() << ":G";
|
|
global = new SaturatingCounterPred(global_name.str(), zero_name, one_name,
|
|
0, _global_bits, 1, 1, _global_thresh);
|
|
}
|
|
|
|
void HybridPredictor::regStats()
|
|
{
|
|
using namespace Stats;
|
|
|
|
string p_name;
|
|
stringstream description;
|
|
|
|
if (reg_individual_stats)
|
|
p_name = pred_name + ":A";
|
|
else
|
|
p_name = pred_name;
|
|
|
|
|
|
//
|
|
// Number of predictions
|
|
//
|
|
stringstream num_zero_preds;
|
|
num_zero_preds << p_name << ":" << zero_name << ":preds";
|
|
description << "number of predictions of " << zero_name;
|
|
pred_zero
|
|
.name(num_zero_preds.str())
|
|
.desc(description.str());
|
|
description.str("");
|
|
|
|
stringstream num_one_preds;
|
|
num_one_preds << p_name << ":" << one_name << ":preds";
|
|
description << "number of predictions of " << one_name;
|
|
pred_one
|
|
.name(num_one_preds.str())
|
|
.desc(description.str())
|
|
;
|
|
description.str("");
|
|
|
|
//
|
|
// Count the number of correct predictions
|
|
//
|
|
stringstream num_zero_correct;
|
|
num_zero_correct << p_name << ":" << zero_name << ":corr_preds";
|
|
description << "number of correct " << zero_name << " preds" ;
|
|
correct_pred_zero
|
|
.name(num_zero_correct.str())
|
|
.desc(description.str())
|
|
;
|
|
description.str("");
|
|
|
|
stringstream num_one_correct;
|
|
num_one_correct << p_name << ":" << one_name << ":corr_preds";
|
|
description << "number of correct " << one_name << " preds" ;
|
|
correct_pred_one
|
|
.name(num_one_correct.str())
|
|
.desc(description.str())
|
|
;
|
|
description.str("");
|
|
|
|
|
|
//
|
|
// Number of predictor updates
|
|
//
|
|
stringstream num_zero_updates;
|
|
num_zero_updates << p_name << ":" << zero_name << ":updates" ;
|
|
description << "number of actual " << zero_name << "s" ;
|
|
record_zero
|
|
.name(num_zero_updates.str())
|
|
.desc(description.str())
|
|
;
|
|
description.str("");
|
|
|
|
stringstream num_one_updates;
|
|
num_one_updates << p_name << ":" << one_name << ":updates" ;
|
|
description << "number of actual " << one_name << "s" ;
|
|
record_one
|
|
.name(num_one_updates.str())
|
|
.desc(description.str())
|
|
;
|
|
description.str("");
|
|
|
|
//
|
|
// Local & Global predictor stats
|
|
//
|
|
if (reg_individual_stats) {
|
|
local->regStats();
|
|
global->regStats();
|
|
}
|
|
}
|
|
|
|
void HybridPredictor::regFormulas()
|
|
{
|
|
using namespace Stats;
|
|
|
|
string p_name;
|
|
stringstream description;
|
|
stringstream name;
|
|
|
|
if (reg_individual_stats)
|
|
p_name = pred_name + ":A";
|
|
else
|
|
p_name = pred_name;
|
|
|
|
//
|
|
// Number of predictions
|
|
//
|
|
name << p_name << ":predictions" ;
|
|
total_preds
|
|
.name(name.str())
|
|
.desc("total number of predictions made")
|
|
;
|
|
total_preds = pred_one + pred_zero;
|
|
name.str("");
|
|
|
|
//
|
|
// Fraction of all predictions that are one or zero
|
|
//
|
|
name << p_name << ":" << zero_name << ":pred_frac";
|
|
description << "fraction of all preds that were " << zero_name ;
|
|
frac_preds_zero
|
|
.name(name.str())
|
|
.desc(description.str())
|
|
;
|
|
frac_preds_zero = 100 * record_zero / total_preds;
|
|
description.str("");
|
|
name.str("");
|
|
|
|
name << p_name << ":" << one_name << ":pred_frac";
|
|
description << "fraction of all preds that were " << one_name ;
|
|
frac_preds_one
|
|
.name(name.str())
|
|
.desc(description.str())
|
|
;
|
|
frac_preds_one = 100 * record_one / total_preds;
|
|
description.str("");
|
|
name.str("");
|
|
|
|
//
|
|
// Count the number of correct predictions
|
|
//
|
|
name << p_name << ":correct_preds" ;
|
|
total_correct
|
|
.name(name.str())
|
|
.desc("total number of correct predictions made")
|
|
;
|
|
total_correct = correct_pred_one + correct_pred_zero;
|
|
name.str("");
|
|
|
|
|
|
//
|
|
// Prediction accuracy rates
|
|
//
|
|
name << p_name << ":pred_rate";
|
|
total_accuracy
|
|
.name(name.str())
|
|
.desc("fraction of all preds that were correct")
|
|
;
|
|
total_accuracy = 100 * total_correct / total_preds;
|
|
name.str("");
|
|
|
|
name << p_name << ":" << zero_name << ":pred_rate" ;
|
|
description << "fraction of "<< zero_name <<" preds that were correct";
|
|
zero_accuracy
|
|
.name(name.str())
|
|
.desc(description.str())
|
|
;
|
|
zero_accuracy = 100 * correct_pred_zero / pred_zero;
|
|
description.str("");
|
|
name.str("");
|
|
|
|
name << p_name << ":" << one_name << ":pred_rate" ;
|
|
description << "fraction of "<< one_name <<" preds that were correct";
|
|
one_accuracy
|
|
.name(name.str())
|
|
.desc(description.str())
|
|
;
|
|
one_accuracy = 100 * correct_pred_one / pred_one;
|
|
description.str("");
|
|
name.str("");
|
|
|
|
//
|
|
// Coverage
|
|
//
|
|
name << p_name << ":" << zero_name << ":coverage";
|
|
description << "fraction of " << zero_name
|
|
<< "s that were predicted correctly";
|
|
zero_coverage
|
|
.name(name.str())
|
|
.desc(description.str())
|
|
;
|
|
zero_coverage = 100 * correct_pred_zero / record_zero;
|
|
description.str("");
|
|
name.str("");
|
|
|
|
name << p_name << ":" << one_name << ":coverage";
|
|
description << "fraction of " << one_name
|
|
<< "s that were predicted correctly";
|
|
one_coverage
|
|
.name(name.str())
|
|
.desc(description.str())
|
|
;
|
|
one_coverage = 100 * correct_pred_one / record_one;
|
|
description.str("");
|
|
name.str("");
|
|
|
|
//
|
|
// Local & Global predictor stats
|
|
//
|
|
if (reg_individual_stats) {
|
|
local->regFormulas();
|
|
global->regFormulas();
|
|
}
|
|
|
|
}
|
|
|