diff options
Diffstat (limited to 'util/plot_dram/dram_sweep_plot.py')
| -rwxr-xr-x | util/plot_dram/dram_sweep_plot.py | 193 |
1 files changed, 193 insertions, 0 deletions
diff --git a/util/plot_dram/dram_sweep_plot.py b/util/plot_dram/dram_sweep_plot.py new file mode 100755 index 000000000..5eb18b95a --- /dev/null +++ b/util/plot_dram/dram_sweep_plot.py @@ -0,0 +1,193 @@ +#!/usr/bin/env python2 + +# 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. +# +# Authors: Andreas Hansson + +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=.1, aspect=10) + + plt.show() + +if __name__ == "__main__": + main() |