util: Add script to plot DRAM low power sweep

This change adds a script to generate graphs from the stats file
output by the configuration script low_power_sweep.py.

The graphs show stacked bars for time spent and energy consumed
wherein each component of the stacked bar represents a DRAM power
state (Idle, Refresh, Active, Active Power-down, Precharge Power-down
and Self-refresh). The script generates one plot per delay value. It
also generates a pdf (--pdf option) in which the graphs are laid out
such that you can easily compare how the increasing delay and other
swept params affect the resulting energy.

Change-Id: Id80b0947bfde27e11e5505b23a3adb30f793a43f
Reviewed-by: Wendy Elsasser <wendy.elsasser@arm.com>
Reviewed-on: https://gem5-review.googlesource.com/5727
Reviewed-by: Andreas Sandberg <andreas.sandberg@arm.com>
Maintainer: Andreas Sandberg <andreas.sandberg@arm.com>

1 files changed, 308 insertions, 0 deletions

diff --git a/util/plot_dram/PlotPowerStates.py b/util/plot_dram/PlotPowerStates.py
new file mode 100755
index 000000000..8dca0e069
--- /dev/null
+++ b/util/plot_dram/PlotPowerStates.py
@@ -0,0 +1,308 @@
+# Copyright (c) 2017 ARM Limited
+# All rights reserved
+#
+# The license below extends only to copyright in the software and shall
+# not be construed as granting a license to any other intellectual
+# property including but not limited to intellectual property relating
+# to a hardware implementation of the functionality of the software
+# licensed hereunder.  You may use the software subject to the license
+# terms below provided that you ensure that this notice is replicated
+# unmodified and in its entirety in all distributions of the software,
+# modified or unmodified, in source code or in binary form.
+#
+# 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: Radhika Jagtap
+
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+from matplotlib.font_manager import FontProperties
+import numpy as np
+import os
+
+# global results dict
+results = {}
+idleResults = {}
+
+# global vars for bank utilisation and seq_bytes values swept in the experiment
+bankUtilValues = []
+seqBytesValues = []
+delayValues = []
+
+# settings for 3 values of bank util and 3 values of seq_bytes
+stackHeight = 6.0
+stackWidth = 18.0
+barWidth = 0.5
+plotFontSize = 18
+
+States = ['IDLE', 'ACT', 'REF', 'ACT_PDN', 'PRE_PDN', 'SREF']
+
+EnergyStates = ['ACT_E',
+'PRE_E',
+'READ_E',
+'REF_E',
+'ACT_BACK_E',
+'PRE_BACK_E',
+'ACT_PDN_E',
+'PRE_PDN_E',
+'SREF_E']
+
+StackColors = {
+'IDLE' : 'black',       # time spent in states
+'ACT' : 'lightskyblue',
+'REF' : 'limegreen',
+'ACT_PDN' : 'crimson',
+'PRE_PDN' : 'orange',
+'SREF' : 'gold',
+'ACT_E' : 'lightskyblue',  # energy of states
+'PRE_E' : 'black',
+'READ_E' : 'white',
+'REF_E' : 'limegreen',
+'ACT_BACK_E' : 'lightgray',
+'PRE_BACK_E' : 'gray',
+'ACT_PDN_E' : 'crimson',
+'PRE_PDN_E' : 'orange',
+'SREF_E' : 'gold'
+}
+
+StatToKey = {
+'system.mem_ctrls_0.actEnergy'          : 'ACT_E',
+'system.mem_ctrls_0.preEnergy'          : 'PRE_E',
+'system.mem_ctrls_0.readEnergy'         : 'READ_E',
+'system.mem_ctrls_0.refreshEnergy'      : 'REF_E',
+'system.mem_ctrls_0.actBackEnergy'      : 'ACT_BACK_E',
+'system.mem_ctrls_0.preBackEnergy'      : 'PRE_BACK_E',
+'system.mem_ctrls_0.actPowerDownEnergy' : 'ACT_PDN_E',
+'system.mem_ctrls_0.prePowerDownEnergy' : 'PRE_PDN_E',
+'system.mem_ctrls_0.selfRefreshEnergy'  : 'SREF_E'
+}
+# Skipping write energy, the example script issues 100% reads by default
+# 'system.mem_ctrls_0.writeEnergy' : "WRITE"
+
+def plotLowPStates(plot_dir, stats_fname, bank_util_list, seqbytes_list,
+                   delay_list):
+    """
+    plotLowPStates generates plots by parsing statistics output by the DRAM
+    sweep simulation described in the the configs/dram/low_power_sweep.py
+    script.
+
+    The function outputs eps format images for the following plots
+    (1) time spent in the DRAM Power states as a stacked bar chart
+    (2) energy consumed by the DRAM Power states as a stacked bar chart
+    (3) idle plot for the last stats dump corresponding to an idle period
+
+    For all plots, the time and energy values of the first rank (i.e. rank0)
+    are plotted because the way the script is written means stats across ranks
+    are similar.
+
+    @param plot_dir: the dir to output the plots
+    @param stats_fname: the stats file name of the low power sweep sim
+    @param bank_util_list: list of bank utilisation values (e.g. [1, 4, 8])
+    @param seqbytes_list: list of seq_bytes values (e.g. [64, 456, 512])
+    @param delay_list: list of itt max multipliers (e.g. [1, 20, 200])
+
+    """
+    stats_file = open(stats_fname, 'r')
+
+    global bankUtilValues
+    bankUtilValues = bank_util_list
+
+    global seqBytesValues
+    seqBytesValues = seqbytes_list
+
+    global delayValues
+    delayValues = delay_list
+    initResults()
+
+    # throw away the first two lines of the stats file
+    stats_file.readline()
+    stats_file.readline() # the 'Begin' line
+
+    #######################################
+    # Parse stats file and gather results
+    ########################################
+
+    for delay in delayValues:
+        for bank_util in bankUtilValues:
+            for seq_bytes in seqBytesValues:
+
+                for line in stats_file:
+                    if 'Begin' in line:
+                        break
+
+                    if len(line.strip()) == 0:
+                        continue
+
+                    #### state time values ####
+                    if 'system.mem_ctrls_0.memoryStateTime' in line:
+                        # remove leading and trailing white spaces
+                        line = line.strip()
+                        # Example format:
+                        # 'system.mem_ctrls_0.memoryStateTime::ACT    1000000'
+                        statistic, stime = line.split()[0:2]
+                        # Now grab the state, i.e. 'ACT'
+                        state = statistic.split('::')[1]
+                        # store the value of the stat in the results dict
+                        results[delay][bank_util][seq_bytes][state] = \
+                            int(stime)
+                    #### state energy values ####
+                    elif line.strip().split()[0] in StatToKey.keys():
+                        # Example format:
+                        # system.mem_ctrls_0.actEnergy                 35392980
+                        statistic, e_val = line.strip().split()[0:2]
+                        senergy = int(float(e_val))
+                        state = StatToKey[statistic]
+                        # store the value of the stat in the results dict
+                        results[delay][bank_util][seq_bytes][state] = senergy
+
+    # To add last traffic gen idle period stats to the results dict
+    for line in stats_file:
+        if 'system.mem_ctrls_0.memoryStateTime' in line:
+            line = line.strip() # remove leading and trailing white spaces
+            # Example format:
+            # 'system.mem_ctrls_0.memoryStateTime::ACT    1000000'
+            statistic, stime = line.split()[0:2]
+            # Now grab the state energy, .e.g 'ACT'
+            state = statistic.split('::')[1]
+            idleResults[state] = int(stime)
+            if state == 'ACT_PDN':
+                break
+
+    ########################################
+    # Call plot functions
+    ########################################
+    # one plot per delay value
+    for delay in delayValues:
+        plot_path = plot_dir + delay + '-'
+
+        plotStackedStates(delay, States, 'IDLE', stateTimePlotName(plot_path),
+                          'Time (ps) spent in a power state')
+        plotStackedStates(delay, EnergyStates, 'ACT_E',
+                          stateEnergyPlotName(plot_path),
+                          'Energy (pJ) of a power state')
+    plotIdle(plot_dir)
+
+def plotIdle(plot_dir):
+    """
+    Create a bar chart for the time spent in power states during the idle phase
+
+    @param plot_dir: the dir to output the plots
+    """
+    fig, ax = plt.subplots()
+    width = 0.35
+    ind = np.arange(len(States))
+    l1 = ax.bar(ind, map(lambda x : idleResults[x], States), width)
+
+    ax.xaxis.set_ticks(ind + width/2)
+    ax.xaxis.set_ticklabels(States)
+    ax.set_ylabel('Time (ps) spent in a power state')
+    fig.suptitle("Idle 50 us")
+
+    print "saving plot:", idlePlotName(plot_dir)
+    plt.savefig(idlePlotName(plot_dir), format='eps')
+    plt.close(fig)
+
+def plotStackedStates(delay, states_list, bottom_state, plot_name, ylabel_str):
+    """
+    Create a stacked bar chart for the list that is passed in as arg, which
+    is either time spent or energy consumed in power states.
+
+    @param delay: one plot is output per delay value
+    @param states_list: list of either time or energy state names
+    @param bottom_state: the bottom-most component of the stacked bar
+    @param plot_name: the file name of the image to write the plot to
+    @param ylabel_str: Y-axis label depending on plotting time or energy
+    """
+    fig, ax = plt.subplots(1, len(bankUtilValues), sharey=True)
+    fig.set_figheight(stackHeight)
+    fig.set_figwidth(stackWidth)
+    width = barWidth
+    plt.rcParams.update({'font.size': plotFontSize})
+
+    # Get the number of seq_bytes values
+    N = len(seqBytesValues)
+    ind = np.arange(N)
+
+    for sub_idx, bank_util in enumerate(bankUtilValues):
+
+        l_states = {}
+        p_states = {}
+
+        # Must have a bottom of the stack first
+        state = bottom_state
+
+        l_states[state] = map(lambda x: results[delay][bank_util][x][state],
+                              seqBytesValues)
+        p_states[state] = ax[sub_idx].bar(ind, l_states[state], width,
+                                          color=StackColors[state])
+
+        time_sum = l_states[state]
+        for state in states_list[1:]:
+            l_states[state] = map(lambda x:
+                                  results[delay][bank_util][x][state],
+                                  seqBytesValues)
+            # Now add on top of the bottom = sum of values up until now
+            p_states[state] = ax[sub_idx].bar(ind, l_states[state], width,
+                                              color=StackColors[state],
+                                              bottom=time_sum)
+            # Now add the bit of the stack that we just ploted to the bottom
+            # resulting in a new bottom for the next iteration
+            time_sum = [prev_sum + new_s for prev_sum, new_s in \
+                zip(time_sum, l_states[state])]
+
+        ax[sub_idx].set_title('Bank util %s' % bank_util)
+        ax[sub_idx].xaxis.set_ticks(ind + width/2.)
+        ax[sub_idx].xaxis.set_ticklabels(seqBytesValues, rotation=45)
+        ax[sub_idx].set_xlabel('Seq. bytes')
+        if bank_util == bankUtilValues[0]:
+            ax[sub_idx].set_ylabel(ylabel_str)
+
+    myFontSize='small'
+    fontP = FontProperties()
+    fontP.set_size(myFontSize)
+    fig.legend(map(lambda x: p_states[x], states_list), states_list,
+               prop=fontP)
+
+    plt.savefig(plot_name,  format='eps', bbox_inches='tight')
+    print "saving plot:", plot_name
+    plt.close(fig)
+
+# These plat name functions are also called in the main script
+def idlePlotName(plot_dir):
+    return (plot_dir + 'idle.eps')
+
+def stateTimePlotName(plot_dir):
+    return (plot_dir + 'state-time.eps')
+
+def stateEnergyPlotName(plot_dir):
+    return (plot_dir + 'state-energy.eps')
+
+def initResults():
+    for delay in delayValues:
+        results[delay] = {}
+        for bank_util in bankUtilValues:
+            results[delay][bank_util] = {}
+            for seq_bytes in seqBytesValues:
+                results[delay][bank_util][seq_bytes] = {}