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util: Enable DRAM sweep to print power and efficiency

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This patch enhances the functionality of the DRAM sweep script to not
only plot the bandwidth utilisation, but also total power and power
efficiency. To do so, a command-line switch is added, and a bit more
data extracted from the stats.
This commit is contained in:
Andreas Hansson 2015-08-05 04:36:31 -04:00
parent 646994e599
commit d540ba0325
1 changed files with 64 additions and 20 deletions
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84
util/dram_sweep_plot.py
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@ -57,18 +57,28 @@ import re
# generated by the config/dram/sweep.py script
def main():
if len(sys.argv) != 2:
print "Usage: ", sys.argv[0], " <simout directory>"
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[1] + '/stats.txt', 'r')
stats = open(sys.argv[2] + '/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')
simout = open(sys.argv[2] + '/simout', 'r')
except IOError:
print "Failed to open ", sys.argv[1] + '/simout', " for reading"
exit(-1)
@ -92,29 +102,57 @@ def main():
print "Failed to establish sweep details, ensure simout is up-to-date"
exit(-1)
# Now parse the stats
peak_bw = []
bus_util = []
avg_pwr = []
# Collect the bus utilisation as our Z-axis, we do this in a 2D
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
# 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
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)
stats.close()
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:
@ -140,7 +178,13 @@ def main():
ax.set_xlabel('Bytes per activate')
ax.set_ylabel('Banks')
ax.set_zlabel('Efficiency (%)')
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)