diff options
| -rw-r--r-- | configs/dram/sweep.py | 13 | ||||
| -rwxr-xr-x | util/dram_sweep_plot.py | 151 |
2 files changed, 161 insertions, 3 deletions
diff --git a/configs/dram/sweep.py b/configs/dram/sweep.py index c1ee0ceca..9b7cfd35e 100644 --- a/configs/dram/sweep.py +++ b/configs/dram/sweep.py @@ -124,12 +124,16 @@ itt = system.mem_ctrls[0].tBURST.value * 1000000000000 # assume we start at 0 max_addr = mem_range.end +# use min of the page size and 512 bytes as that should be more than +# enough +max_stride = min(512, page_size) + # now we create the state by iterating over the stride size from burst -# size to min of the page size and 1 kB, and from using only a single -# bank up to the number of banks available +# size to the max stride, and from using only a single bank up to the +# number of banks available nxt_state = 0 for bank in range(1, nbr_banks + 1): - for stride_size in range(burst_size, min(1024, page_size) + 1, burst_size): + for stride_size in range(burst_size, max_stride + 1, burst_size): cfg_file.write("STATE %d %d DRAM 100 0 %d " "%d %d %d %d %d %d %d %d 1\n" % (nxt_state, period, max_addr, burst_size, itt, itt, 0, @@ -168,3 +172,6 @@ root.system.mem_mode = 'timing' m5.instantiate() m5.simulate(nxt_state * period) + +print "DRAM sweep with burst: %d, banks: %d, max stride: %d" % \ + (burst_size, nbr_banks, max_stride) diff --git a/util/dram_sweep_plot.py b/util/dram_sweep_plot.py new file mode 100755 index 000000000..a57de3d1c --- /dev/null +++ b/util/dram_sweep_plot.py @@ -0,0 +1,151 @@ +#!/usr/bin/env python + +# 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 + from matplotlib.ticker import LinearLocator, FormatStrFormatter + 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) != 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 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) + + + # Collect the bus utilisation as our Z-axis, we do this in a 2D + # grid corresponding to each iteration over the various stride + # sizes. + z = [] + zs = [] + i = 0 + + # Now parse the stats + for line in stats: + match = re.match(".*busUtil\s+(\d+\.\d+)\s+#.*", line) + if match: + bus_util = float(match.groups(0)[0]) + z.append(bus_util) + 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 + + stats.close() + + # 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') + ax.set_zlabel('Efficiency (%)') + + # Add a colorbar + fig.colorbar(surf, shrink=0.5, pad=.1, aspect=10) + + plt.show() + +if __name__ == "__main__": + main() |