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Diffstat (limited to 'sim/hybrid_pred.cc')
| -rw-r--r-- | sim/hybrid_pred.cc | 275 |
1 files changed, 275 insertions, 0 deletions
diff --git a/sim/hybrid_pred.cc b/sim/hybrid_pred.cc new file mode 100644 index 000000000..6a8384083 --- /dev/null +++ b/sim/hybrid_pred.cc @@ -0,0 +1,275 @@ +/* + * Copyright (c) 2003 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. + */ + +#include <string> +#include <sstream> + +#include "stats.hh" +#include "hybrid_pred.hh" + +#include "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 Statistics; + + 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 Statistics; + + 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(); + } + +} + |