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authorRadhika Jagtap <radhika.jagtap@arm.com>2017-06-21 11:17:43 +0100
committerAndreas Sandberg <andreas.sandberg@arm.com>2017-11-16 16:39:19 +0000
commit9b4e797cdd7e10ace8de83626ea844a6acabcafb (patch)
tree88547cd0654d49f48bf1f648608961fc964e2302 /util/plot_dram/dram_lat_mem_rd_plot.py
parent1695c9933b53a606ba7044e1b2dfcfe8c203018e (diff)
downloadgem5-9b4e797cdd7e10ace8de83626ea844a6acabcafb.tar.xz
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>
Diffstat (limited to 'util/plot_dram/dram_lat_mem_rd_plot.py')
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1 files changed, 151 insertions, 0 deletions
diff --git a/util/plot_dram/dram_lat_mem_rd_plot.py b/util/plot_dram/dram_lat_mem_rd_plot.py
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+++ b/util/plot_dram/dram_lat_mem_rd_plot.py
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+#!/usr/bin/env python2
+
+# Copyright (c) 2015 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: Andreas Hansson
+
+try:
+ import matplotlib.pyplot as plt
+ import matplotlib as mpl
+ import numpy as np
+except ImportError:
+ print "Failed to import matplotlib and numpy"
+ exit(-1)
+
+import sys
+import re
+
+# This script is intended to post process and plot the output from
+# running configs/dram/lat_mem_rd.py, as such it parses the simout and
+# stats.txt to get the relevant data points.
+def main():
+
+ if len(sys.argv) != 2:
+ print "Usage: ", sys.argv[0], "<simout directory>"
+ exit(-1)
+
+ try:
+ stats = open(sys.argv[1] + '/stats.txt', 'r')
+ except IOError:
+ print "Failed to open ", sys.argv[1] + '/stats.txt', " for reading"
+ exit(-1)
+
+ try:
+ simout = open(sys.argv[1] + '/simout', 'r')
+ except IOError:
+ print "Failed to open ", sys.argv[1] + '/simout', " for reading"
+ exit(-1)
+
+ # Get the address ranges
+ got_ranges = False
+ ranges = []
+
+ iterations = 1
+
+ for line in simout:
+ if got_ranges:
+ ranges.append(int(line) / 1024)
+
+ match = re.match("lat_mem_rd with (\d+) iterations, ranges:.*", line)
+ if match:
+ got_ranges = True
+ iterations = int(match.groups(0)[0])
+
+ simout.close()
+
+ if not got_ranges:
+ print "Failed to get address ranges, ensure simout is up-to-date"
+ exit(-1)
+
+ # Now parse the stats
+ raw_rd_lat = []
+
+ for line in stats:
+ match = re.match(".*readLatencyHist::mean\s+(.+)\s+#.*", line)
+ if match:
+ raw_rd_lat.append(float(match.groups(0)[0]) / 1000)
+ stats.close()
+
+ # The stats also contain the warming, so filter the latency stats
+ i = 0
+ filtered_rd_lat = []
+ for l in raw_rd_lat:
+ if i % (iterations + 1) == 0:
+ pass
+ else:
+ filtered_rd_lat.append(l)
+ i = i + 1
+
+ # Next we need to take care of the iterations
+ rd_lat = []
+ for i in range(iterations):
+ rd_lat.append(filtered_rd_lat[i::iterations])
+
+ final_rd_lat = map(lambda p: min(p), zip(*rd_lat))
+
+ # Sanity check
+ if not (len(ranges) == len(final_rd_lat)):
+ print "Address ranges (%d) and read latency (%d) do not match" % \
+ (len(ranges), len(final_rd_lat))
+ exit(-1)
+
+ for (r, l) in zip(ranges, final_rd_lat):
+ print r, round(l, 2)
+
+ # lazy version to check if an integer is a power of two
+ def is_pow2(num):
+ return num != 0 and ((num & (num - 1)) == 0)
+
+ plt.semilogx(ranges, final_rd_lat)
+
+ # create human readable labels
+ xticks_locations = [r for r in ranges if is_pow2(r)]
+ xticks_labels = []
+ for x in xticks_locations:
+ if x < 1024:
+ xticks_labels.append('%d kB' % x)
+ else:
+ xticks_labels.append('%d MB' % (x / 1024))
+ plt.xticks(xticks_locations, xticks_labels, rotation=-45)
+
+ plt.minorticks_off()
+ plt.xlim((xticks_locations[0], xticks_locations[-1]))
+ plt.ylabel("Latency (ns)")
+ plt.grid(True)
+ plt.show()
+
+if __name__ == "__main__":
+ main()