| # SPDX-License-Identifier: Apache-2.0 |
| # |
| # Copyright (C) 2015, ARM Limited and contributors. |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); you may |
| # not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT |
| # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| import glob |
| import matplotlib.gridspec as gridspec |
| import matplotlib.pyplot as plt |
| import numpy as np |
| import os |
| import pandas as pd |
| import pylab as pl |
| import re |
| import sys |
| import trappy |
| import logging |
| |
| # Regexp to match an rt-app generated logfile |
| TASK_NAME_RE = re.compile('.*\/rt-app-(.+)-[0-9]+.log') |
| |
| class PerfAnalysis(object): |
| |
| def __init__(self, datadir, tasks=None): |
| |
| # Dataframe of all tasks performance data |
| self.perf_data = {} |
| |
| # Folder containing all rt-app data |
| self.datadir = None |
| |
| # Setup logging |
| self._log = logging.getLogger('PerfAnalysis') |
| |
| # Load performance data generated by rt-app workloads |
| self.__loadRTAData(datadir, tasks) |
| |
| # Keep track of the datadir from where data have been loaded |
| if len(self.perf_data) == 0: |
| raise ValueError('No performance data found on folder [{0:s}]'\ |
| .format(datadir)) |
| |
| self.datadir = datadir |
| |
| def __taskNameFromLog(self, logfile): |
| tname_match = re.search(TASK_NAME_RE, logfile) |
| if tname_match is None: |
| raise ValueError('The logfile [{0:s}] is not from rt-app'\ |
| .format(logfile)) |
| return tname_match.group(1) |
| |
| def __logfileFromTaskName(self, taskname): |
| for logfile in glob.glob( |
| '{0:s}/rt-app-{1:s}.log'.format(self.datadir, taskname)): |
| return logfile |
| raise ValueError('No rt-app logfile found for task [{0:s}]'\ |
| .format(taskname)) |
| |
| def tasks(self): |
| """ |
| Return the list of tasks for which performance data have been loaded |
| """ |
| if self.datadir is None: |
| raise ValueError("rt-app performance data not (yet) loaded") |
| return self.perf_data.keys() |
| |
| def logfile(self, task): |
| """ |
| Return the logfile for the specified task |
| """ |
| if task not in self.perf_data: |
| raise ValueError('No logfile loaded for task [{0:s}]'\ |
| .format(task)) |
| return self.perf_data[task]['logfile'] |
| |
| def df(self, task): |
| """ |
| Return the PANDAS dataframe with the performance data for the |
| specified task |
| """ |
| if self.datadir is None: |
| raise ValueError("rt-app performance data not (yet) loaded") |
| if task not in self.perf_data: |
| raise ValueError('No dataframe loaded for task [{0:s}]'\ |
| .format(task)) |
| return self.perf_data[task]['df'] |
| |
| def __loadRTAData(self, datadir, tasks): |
| """ |
| Load peformance data of an rt-app workload |
| """ |
| |
| if tasks is None: |
| # Lookup for all rt-app logfile into the specified datadir |
| for logfile in glob.glob('{0:s}/rt-app-*.log'.format(datadir)): |
| task_name = self.__taskNameFromLog(logfile) |
| self.perf_data[task_name] = {} |
| self.perf_data[task_name]['logfile'] = logfile |
| self._log.debug('Found rt-app logfile for task [%s]', task_name) |
| else: |
| # Lookup for specified rt-app task logfile into specified datadir |
| for task in tasks: |
| logfile = self.__logfileFromTaskName(task) |
| self.perf_data[task_name] = {} |
| self.perf_data[task_name]['logfile'] = logfile |
| self._log.debug('Found rt-app logfile for task [%s]', task_name) |
| |
| # Load all the found logfile into a dataset |
| for task in self.perf_data.keys(): |
| self._log.debug('Loading dataframe for task [%s]...', task) |
| df = pd.read_table(self.logfile(task), |
| sep='\s+', |
| skiprows=1, |
| header=0, |
| usecols=[1,2,3,4,7,8,9,10], |
| names=[ |
| 'Cycles', 'Run' ,'Period', 'Timestamp', |
| 'Slack', 'CRun', 'CPeriod', 'WKPLatency' |
| ]) |
| # Normalize time to [s] with origin on the first event |
| start_time = df['Timestamp'][0]/1e6 |
| df['Time'] = df['Timestamp']/1e6 - start_time |
| df.set_index(['Time'], inplace=True) |
| # Add performance metrics column, performance is defined as: |
| # slack |
| # perf = ------------- |
| # period - run |
| df['PerfIndex'] = df['Slack'] / (df['CPeriod'] - df['CRun']) |
| |
| # Keep track of the loaded dataframe |
| self.perf_data[task]['df'] = df |
| |
| def plotPerf(self, task, title=None): |
| """ |
| Plot the Latency/Slack and Performance data for the specified task |
| """ |
| # Grid |
| gs = gridspec.GridSpec(2, 2, height_ratios=[4,1], width_ratios=[3,1]); |
| gs.update(wspace=0.1, hspace=0.1); |
| # Figure |
| plt.figure(figsize=(16, 2*6)); |
| if title: |
| plt.suptitle(title, y=.97, fontsize=16, |
| horizontalalignment='center'); |
| # Plot: Slack and Latency |
| axes = plt.subplot(gs[0,0]); |
| axes.set_title('Task [{0:s}] (start) Latency and (completion) Slack'\ |
| .format(task)); |
| data = self.df(task)[['Slack', 'WKPLatency']] |
| data.plot(ax=axes, drawstyle='steps-post', style=['r', 'g']); |
| # axes.set_xlim(x_min, x_max); |
| axes.xaxis.set_visible(False); |
| # Plot: Performance |
| axes = plt.subplot(gs[1,0]); |
| axes.set_title('Task [{0:s}] Performance Index'.format(task)); |
| data = self.df(task)[['PerfIndex',]] |
| data.plot(ax=axes, drawstyle='steps-post'); |
| axes.set_ylim(0, 2); |
| # axes.set_xlim(x_min, x_max); |
| # Plot: Slack Histogram |
| axes = plt.subplot(gs[0:2,1]); |
| data = self.df(task)[['PerfIndex',]] |
| data.hist(bins=30, ax=axes, alpha=0.4); |
| # axes.set_xlim(x_min, x_max); |
| pindex_avg = data.mean()[0]; |
| pindex_std = data.std()[0]; |
| self._log.info('PerfIndex, Task [%s] avg: %.2f, std: %.2f', |
| task, pindex_avg, pindex_std) |
| axes.axvline(pindex_avg, color='b', linestyle='--', linewidth=2); |
| |
| |
| # Save generated plots into datadir |
| figname = '{}/task_perf_{}.png'.format(self.datadir, task) |
| pl.savefig(figname, bbox_inches='tight') |
| |
