cachepc-qemu

Fork of AMDESE/qemu with changes for cachepc side-channel attack
git clone https://git.sinitax.com/sinitax/cachepc-qemu
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results_to_text.py (3808B)

      1#!/usr/bin/env python3
      2#
      3# Simple benchmarking framework
      4#
      5# Copyright (c) 2019 Virtuozzo International GmbH.
      6#
      7# This program is free software; you can redistribute it and/or modify
      8# it under the terms of the GNU General Public License as published by
      9# the Free Software Foundation; either version 2 of the License, or
     10# (at your option) any later version.
     11#
     12# This program is distributed in the hope that it will be useful,
     13# but WITHOUT ANY WARRANTY; without even the implied warranty of
     14# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
     15# GNU General Public License for more details.
     16#
     17# You should have received a copy of the GNU General Public License
     18# along with this program.  If not, see <http://www.gnu.org/licenses/>.
     19#
     20
     21import math
     22import tabulate
     23
     24# We want leading whitespace for difference row cells (see below)
     25tabulate.PRESERVE_WHITESPACE = True
     26
     27
     28def format_value(x, stdev):
     29    stdev_pr = stdev / x * 100
     30    if stdev_pr < 1.5:
     31        # don't care too much
     32        return f'{x:.2g}'
     33    else:
     34        return f'{x:.2g} ± {math.ceil(stdev_pr)}%'
     35
     36
     37def result_to_text(result):
     38    """Return text representation of bench_one() returned dict."""
     39    if 'average' in result:
     40        s = format_value(result['average'], result['stdev'])
     41        if 'n-failed' in result:
     42            s += '\n({} failed)'.format(result['n-failed'])
     43        return s
     44    else:
     45        return 'FAILED'
     46
     47
     48def results_dimension(results):
     49    dim = None
     50    for case in results['cases']:
     51        for env in results['envs']:
     52            res = results['tab'][case['id']][env['id']]
     53            if dim is None:
     54                dim = res['dimension']
     55            else:
     56                assert dim == res['dimension']
     57
     58    assert dim in ('iops', 'seconds')
     59
     60    return dim
     61
     62
     63def results_to_text(results):
     64    """Return text representation of bench() returned dict."""
     65    n_columns = len(results['envs'])
     66    named_columns = n_columns > 2
     67    dim = results_dimension(results)
     68    tab = []
     69
     70    if named_columns:
     71        # Environment columns are named A, B, ...
     72        tab.append([''] + [chr(ord('A') + i) for i in range(n_columns)])
     73
     74    tab.append([''] + [c['id'] for c in results['envs']])
     75
     76    for case in results['cases']:
     77        row = [case['id']]
     78        case_results = results['tab'][case['id']]
     79        for env in results['envs']:
     80            res = case_results[env['id']]
     81            row.append(result_to_text(res))
     82        tab.append(row)
     83
     84        # Add row of difference between columns. For each column starting from
     85        # B we calculate difference with all previous columns.
     86        row = ['', '']  # case name and first column
     87        for i in range(1, n_columns):
     88            cell = ''
     89            env = results['envs'][i]
     90            res = case_results[env['id']]
     91
     92            if 'average' not in res:
     93                # Failed result
     94                row.append(cell)
     95                continue
     96
     97            for j in range(0, i):
     98                env_j = results['envs'][j]
     99                res_j = case_results[env_j['id']]
    100                cell += ' '
    101
    102                if 'average' not in res_j:
    103                    # Failed result
    104                    cell += '--'
    105                    continue
    106
    107                col_j = tab[0][j + 1] if named_columns else ''
    108                diff_pr = round((res['average'] - res_j['average']) /
    109                                res_j['average'] * 100)
    110                cell += f' {col_j}{diff_pr:+}%'
    111            row.append(cell)
    112        tab.append(row)
    113
    114    return f'All results are in {dim}\n\n' + tabulate.tabulate(tab)
    115
    116
    117if __name__ == '__main__':
    118    import sys
    119    import json
    120
    121    if len(sys.argv) < 2:
    122        print(f'USAGE: {sys.argv[0]} results.json')
    123        exit(1)
    124
    125    with open(sys.argv[1]) as f:
    126        print(results_to_text(json.load(f)))