util/plot_dram/dram_sweep_plot.py - public/gem5 - Git at Google

 #!/usr/bin/env python3

 # Copyright (c) 2014 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.

 try:
     from mpl_toolkits.mplot3d import Axes3D
     from matplotlib import cm
     import matplotlib.pyplot as plt
     import numpy as np
 except ImportError:
     print("Failed to import matplotlib and numpy")
     exit(-1)

 import sys
 import re

 # Determine the parameters of the sweep from the simout output, and
 # then parse the stats and plot the 3D surface corresponding to the
 # different combinations of parallel banks, and stride size, as
 # generated by the config/dram/sweep.py script
 def main():

     if len(sys.argv) != 3:
         print("Usage: ", sys.argv[0], "-u|p|e <simout directory>")
         exit(-1)

     if (
         len(sys.argv[1]) != 2
         or sys.argv[1][0] != "-"
         or not sys.argv[1][1] in "upe"
     ):
         print(
             "Choose -u (utilisation), -p (total power), or -e "
             "(power efficiency)"
         )
         exit(-1)

     # Choose the appropriate mode, either utilisation, total power, or
     # efficiency
     mode = sys.argv[1][1]

     try:
         stats = open(sys.argv[2] + "/stats.txt", "r")
     except IOError:
         print("Failed to open ", sys.argv[2] + "/stats.txt", " for reading")
         exit(-1)

     try:
         simout = open(sys.argv[2] + "/simout", "r")
     except IOError:
         print("Failed to open ", sys.argv[2] + "/simout", " for reading")
         exit(-1)

     # Get the burst size, number of banks and the maximum stride from
     # the simulation output
     got_sweep = False

     for line in simout:
         match = re.match(
             "DRAM sweep with burst: (\d+), banks: (\d+), max stride: (\d+)",
             line,
         )
         if match:
             burst_size = int(match.groups(0)[0])
             banks = int(match.groups(0)[1])
             max_size = int(match.groups(0)[2])
             got_sweep = True

     simout.close()

     if not got_sweep:
         print("Failed to establish sweep details, ensure simout is up-to-date")
         exit(-1)

     # Now parse the stats
     peak_bw = []
     bus_util = []
     avg_pwr = []

     for line in stats:
         match = re.match(".*busUtil\s+(\d+\.\d+)\s+#.*", line)
         if match:
             bus_util.append(float(match.groups(0)[0]))

         match = re.match(".*peakBW\s+(\d+\.\d+)\s+#.*", line)
         if match:
             peak_bw.append(float(match.groups(0)[0]))

         match = re.match(".*averagePower\s+(\d+\.?\d*)\s+#.*", line)
         if match:
             avg_pwr.append(float(match.groups(0)[0]))
     stats.close()

     # Sanity check
     if not (len(peak_bw) == len(bus_util) and len(bus_util) == len(avg_pwr)):
         print(
             "Peak bandwidth, bus utilisation, and average power do not match"
         )
         exit(-1)

     # Collect the selected metric as our Z-axis, we do this in a 2D
     # grid corresponding to each iteration over the various stride
     # sizes.
     z = []
     zs = []
     i = 0

     for j in range(len(peak_bw)):
         if mode == "u":
             z.append(bus_util[j])
         elif mode == "p":
             z.append(avg_pwr[j])
         elif mode == "e":
             # avg_pwr is in mW, peak_bw in MiByte/s, bus_util in percent
             z.append(avg_pwr[j] / (bus_util[j] / 100.0 * peak_bw[j] / 1000.0))
         else:
             print("Unexpected mode %s" % mode)
             exit(-1)

         i += 1
         # If we have completed a sweep over the stride sizes,
         # start anew
         if i == max_size / burst_size:
             zs.append(z)
             z = []
             i = 0

     # We should have a 2D grid with as many columns as banks
     if len(zs) != banks:
         print("Unexpected number of data points in stats output")
         exit(-1)

     fig = plt.figure()
     ax = fig.gca(projection="3d")
     X = np.arange(burst_size, max_size + 1, burst_size)
     Y = np.arange(1, banks + 1, 1)
     X, Y = np.meshgrid(X, Y)

     # the values in the util are banks major, so we see groups for each
     # stride size in order
     Z = np.array(zs)

     surf = ax.plot_surface(
         X,
         Y,
         Z,
         rstride=1,
         cstride=1,
         cmap=cm.coolwarm,
         linewidth=0,
         antialiased=False,
     )

     # Change the tick frequency to 64
     start, end = ax.get_xlim()
     ax.xaxis.set_ticks(np.arange(start, end + 1, 64))

     ax.set_xlabel("Bytes per activate")
     ax.set_ylabel("Banks")

     if mode == "u":
         ax.set_zlabel("Utilisation (%)")
     elif mode == "p":
         ax.set_zlabel("Power (mW)")
     elif mode == "e":
         ax.set_zlabel("Power efficiency (mW / GByte / s)")

     # Add a colorbar
     fig.colorbar(surf, shrink=0.5, pad=0.1, aspect=10)

     plt.show()


 if __name__ == "__main__":
     main()
	#!/usr/bin/env python3

	# Copyright (c) 2014 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.

	try:
	from mpl_toolkits.mplot3d import Axes3D
	from matplotlib import cm
	import matplotlib.pyplot as plt
	import numpy as np
	except ImportError:
	print("Failed to import matplotlib and numpy")
	exit(-1)

	import sys
	import re

	# Determine the parameters of the sweep from the simout output, and
	# then parse the stats and plot the 3D surface corresponding to the
	# different combinations of parallel banks, and stride size, as
	# generated by the config/dram/sweep.py script
	def main():

	if len(sys.argv) != 3:
	print("Usage: ", sys.argv[0], "-u\|p\|e <simout directory>")
	exit(-1)

	if (
	len(sys.argv[1]) != 2
	or sys.argv[1][0] != "-"
	or not sys.argv[1][1] in "upe"
	):
	print(
	"Choose -u (utilisation), -p (total power), or -e "
	"(power efficiency)"
	)
	exit(-1)

	# Choose the appropriate mode, either utilisation, total power, or
	# efficiency
	mode = sys.argv[1][1]

	try:
	stats = open(sys.argv[2] + "/stats.txt", "r")
	except IOError:
	print("Failed to open ", sys.argv[2] + "/stats.txt", " for reading")
	exit(-1)

	try:
	simout = open(sys.argv[2] + "/simout", "r")
	except IOError:
	print("Failed to open ", sys.argv[2] + "/simout", " for reading")
	exit(-1)

	# Get the burst size, number of banks and the maximum stride from
	# the simulation output
	got_sweep = False

	for line in simout:
	match = re.match(
	"DRAM sweep with burst: (\d+), banks: (\d+), max stride: (\d+)",
	line,
	)
	if match:
	burst_size = int(match.groups(0)[0])
	banks = int(match.groups(0)[1])
	max_size = int(match.groups(0)[2])
	got_sweep = True

	simout.close()

	if not got_sweep:
	print("Failed to establish sweep details, ensure simout is up-to-date")
	exit(-1)

	# Now parse the stats
	peak_bw = []
	bus_util = []
	avg_pwr = []

	for line in stats:
	match = re.match(".busUtil\s+(\d+\.\d+)\s+#.", line)
	if match:
	bus_util.append(float(match.groups(0)[0]))

	match = re.match(".peakBW\s+(\d+\.\d+)\s+#.", line)
	if match:
	peak_bw.append(float(match.groups(0)[0]))

	match = re.match(".averagePower\s+(\d+\.?\d)\s+#.*", line)
	if match:
	avg_pwr.append(float(match.groups(0)[0]))
	stats.close()

	# Sanity check
	if not (len(peak_bw) == len(bus_util) and len(bus_util) == len(avg_pwr)):
	print(
	"Peak bandwidth, bus utilisation, and average power do not match"
	)
	exit(-1)

	# Collect the selected metric as our Z-axis, we do this in a 2D
	# grid corresponding to each iteration over the various stride
	# sizes.
	z = []
	zs = []
	i = 0

	for j in range(len(peak_bw)):
	if mode == "u":
	z.append(bus_util[j])
	elif mode == "p":
	z.append(avg_pwr[j])
	elif mode == "e":
	# avg_pwr is in mW, peak_bw in MiByte/s, bus_util in percent
	z.append(avg_pwr[j] / (bus_util[j] / 100.0 * peak_bw[j] / 1000.0))
	else:
	print("Unexpected mode %s" % mode)
	exit(-1)

	i += 1
	# If we have completed a sweep over the stride sizes,
	# start anew
	if i == max_size / burst_size:
	zs.append(z)
	z = []
	i = 0

	# We should have a 2D grid with as many columns as banks
	if len(zs) != banks:
	print("Unexpected number of data points in stats output")
	exit(-1)

	fig = plt.figure()
	ax = fig.gca(projection="3d")
	X = np.arange(burst_size, max_size + 1, burst_size)
	Y = np.arange(1, banks + 1, 1)
	X, Y = np.meshgrid(X, Y)

	# the values in the util are banks major, so we see groups for each
	# stride size in order
	Z = np.array(zs)

	surf = ax.plot_surface(
	X,
	Y,
	Z,
	rstride=1,
	cstride=1,
	cmap=cm.coolwarm,
	linewidth=0,
	antialiased=False,
	)

	# Change the tick frequency to 64
	start, end = ax.get_xlim()
	ax.xaxis.set_ticks(np.arange(start, end + 1, 64))

	ax.set_xlabel("Bytes per activate")
	ax.set_ylabel("Banks")

	if mode == "u":
	ax.set_zlabel("Utilisation (%)")
	elif mode == "p":
	ax.set_zlabel("Power (mW)")
	elif mode == "e":
	ax.set_zlabel("Power efficiency (mW / GByte / s)")

	# Add a colorbar
	fig.colorbar(surf, shrink=0.5, pad=0.1, aspect=10)

	plt.show()


	if __name__ == "__main__":
	main()