def main():
ccbench.controller() # handle CLI options
#handle default/cli args app
app_bin = BASE_DIR + APP
input_filename = BASE_DIR + DEFAULT_INPUT_NAME
report_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR)
# 1. Parse inputs.txt file
if (not ccbench.NORUN):
inputs = ccbench.parseInputFile(input_filename, input_variables,
ccbench.INPUT_TYPE)
NumDataPointsPerSet = 0
# Build up the arguments list for each invocation of the benchmark.
# This is done here, instead of in ccbench.py, because this is custom to each app.
app_args_list = []
for num_threads in inputs["NumThreads"]:
for num_requests in inputs["NumRequests"]:
for app_size in inputs["AppSize"]:
NumDataPointsPerSet += num_threads #each thread spawns a new entry in band_req_mc!
app_args_list.append(str(num_threads) + " " + str(num_requests) + " " + str(app_size) \
+ " " + str(inputs["NumIterations"][0]))
inputs["NumDataPointsPerSet"] = []
inputs["NumDataPointsPerSet"].append(str(NumDataPointsPerSet))
# 2. Execute the benchmark and read the report file
if (not ccbench.NORUN):
ccbench.runBenchmark(app_bin, app_args_list, inputs, input_variables,
report_filename)
# 3. Extract Data
data = ccbench.readReportFile(report_filename, variables)
inputs = ccbench.parseReportFileForInputs(report_filename, input_variables)
# 4. Plot the Data
#print data
if NOPLOT:
return
fig = plt.figure(figsize=(9, 5.5))
p2 = fig.add_subplot(1, 2, 2)
p1 = fig.add_subplot(1, 2, 1)
print "Plotting time..."
num_datapoints = int(data["NumDataPointsPerSet"][0])
# let's convert "appsizearg(#elm)" to "appsize(KB)"
for i in range(len(data["AppSize"])):
data["AppSize"][i] = str(float(data["AppSize"][i]) * 4 / 1024)
# deal with ticks
# xtick_range = [1,2,4,8,16,32,64,128,256,512,1024,2048,4096,4096*2,16384] #for KB
# xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB'] #for KB
xtick_range = [1, 4, 16, 64, 256, 1024, 4096, 16384] #for KB
xtick_names = [
'1 kB', '4 kB', '16 kB', '64 kB', '256 kB', '1 MB', '4 MB', '16 MB'
]
xmin, xmax = plt.xlim()
print "xmax = %d" % (xmax)
# if (xmax >= 1024*32):
# xtick_range = [1,2,4,8,16,32,64, 128,256, 512,1024,2048,4096,4096*2, 16384,16384*2,16384*4,1024*128]
# xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB','32 MB','64 MB','128 MB'] #for KB
xtick_range = [1, 4, 16, 64, 256, 1024, 4096, 16384, 1024 * 64] #for KB
xtick_names = [
'1 kB', '4 kB', '16 kB', '64 kB', '256 kB', '1 MB', '4 MB', '16 MB',
'64 MB'
]
plt.xlim((0.5, 1024 * 128))
# fig.subplots_adjust(top=0.95, bottom=0.12, left=0.07, right=0.90,wspace=0, hspace=0)
fig.subplots_adjust(top=0.95,
bottom=0.12,
left=0.07,
right=0.90,
wspace=0.13,
hspace=0)
c_counter = 0
colors = ('b', 'g', 'r', 'c', 'm', 'y', 'k', 'b', 'g', 'r', 'c', 'm')
line_styles = ('-.', ':', '-.', ':')
for num_threads in inputs["NumThreads"]:
#x_array = [int(s) for s in array ]
# print "NumThreads, graphing NumThreads: " + str(num_threads)
l_counter = 0
color = colors[c_counter % len(colors)]
c_counter += 1
# plot a line for each tid in th eexperiment NumThreads
for num_req in inputs["NumRequests"]:
line_style = line_styles[l_counter % len(line_styles)]
l_counter += 1
for tid in range(num_threads):
x_array = []
band_array = []
aggr_array = []
for idx in range(len(data["AppSize"])):
# print " looking at idx: " + str(idx) + " in data[apsize]"
if (int(data["ThreadID"][idx]) == int(tid)) and (int(
data["NumThreads"][idx]) == num_threads) and (int(
data["NumRequests"][idx]) == num_req):
# print " appending " + data["AppSize"][idx] + " For ThreadID: " + data["ThreadID"][idx]
x_array.append(data["AppSize"][idx])
aggr_array.append(data["AggregateBandwidth"][idx])
band_array.append(data["Bandwidth"][idx])
p1.plot(
x_array,
band_array,
# linestyle="--",
linestyle=line_style,
# linestyle=" ",
marker='.',
color=color)
p2.plot(
x_array,
aggr_array,
# linestyle="--",
linestyle=line_style,
# linestyle=" ",
marker='.',
color=color)
p1.set_xscale('log')
p2.set_xscale('log')
plt.ylabel(data["BandwidthUnits"][0])
plt.xlabel('Per Thread Working Set')
ymin, ymax = plt.ylim()
plt.ylim((0.0, ymax))
plt.xlim((0.5, 16384))
p1.xaxis.set_major_locator(plt.NullLocator())
p1.xaxis.set_minor_locator(plt.NullLocator())
p2.xaxis.set_major_locator(plt.NullLocator())
p2.xaxis.set_minor_locator(plt.NullLocator())
plt.xticks(xtick_range, xtick_names, rotation='-30', size='small')
p2 = fig.add_subplot(1, 2, 2)
plt.xticks(xtick_range, xtick_names, rotation='-30', size='small')
# resize the per thread bandwidth...(to match aggregate bandwidth)
#p2 = fig.add_subplot(1,2,2)
#(ylow,yhigh) = plt.ylim()
#p1 = fig.add_subplot(1,2,1)
#plt.ylim((ylow,yhigh))
# plot processor-specific info
p1 = fig.add_subplot(1, 2, 1)
(ylow, yhigh) = plt.ylim()
yhigh = 0.95 * yhigh
ylow = 0.95 * yhigh
ccprocstats.plotCacheSizeLines(plt, p1, ccbench.PROCESSOR, ylow, yhigh)
p2 = fig.add_subplot(1, 2, 2)
plt.xlabel('Per Thread Working Set')
(ylow, yhigh) = plt.ylim()
yhigh = 0.95 * yhigh
ylow = 0.95 * yhigh
ccprocstats.plotCacheSizeLines(plt, p2, ccbench.PROCESSOR, ylow, yhigh)
p2 = fig.add_subplot(1, 2, 2)
plt.title("Aggregate Bandwidth" + r'', fontstyle='italic')
p1 = fig.add_subplot(1, 2, 1)
plt.title("Per Thread Bandwidth" + r'', fontstyle='italic')
# legend
colors = ('b', 'g', 'r', 'c', 'm', 'y', 'k', 'b', 'g', 'r', 'c', 'm')
legend_sz = len(inputs["NumThreads"])
lines = []
for i in (range(legend_sz)):
lines.append(
plt.Line2D([0, 10], [0, 10],
linewidth=3,
color=colors[legend_sz - 1 - i],
linestyle='-'))
args = range(legend_sz)
for i in (range(legend_sz)):
args[legend_sz - 1 - i] = str(inputs["NumThreads"][i]) + " Threads"
# args[legend_sz - 1 - i] = "{Thds:" + str(inputs["NumThreads"][i]) + "}" #+ ", Reqs:" + input["NumRequests"][((i)*num_datapoints)] + "}"
p2 = fig.add_subplot(1, 2, 2)
plt.legend(lines,
args,
'best',
title="Num of Threads",
bbox_to_anchor=(0.70, 0.9))
(ylow, yhigh) = plt.ylim()
(xmin, xmax) = plt.xlim()
p2.text(xmax,
0.9 * yhigh,
"%d requests / thread" % (inputs["NumRequests"][0]),
horizontalalignment='center',
verticalalignment='center',
size='x-small')
if (ccbench.PLOT_FILENAME == "none"):
filename = PLOT_DIR + ccbench.generatePlotFileName(APP)
else:
# Pull out the filename path from the full path.
# This allows us to pull out the requested filename from the path presented
# (since we always write reports to the report directory, etc.). However, it
# allows the user to use tab-completion to specify the exact reportfile he
# wants to use.
filename = PLOT_DIR + os.path.basename(ccbench.PLOT_FILENAME)
filename = os.path.splitext(filename)[0]
plt.savefig(filename)
print "Used report filename : " + report_filename
print "Finished Plotting, saved as file : " + filename + ".pdf"
def main():
# handle CLI options
ccbench.controller()
#handle default/cli args app
app_bin = BASE_DIR + APP
input_filename = BASE_DIR + DEFAULT_INPUT_NAME
report_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR)
# 1. Parse inputs.txt file.
if (not ccbench.NORUN):
inputs = ccbench.parseInputFile(input_filename, variables,
ccbench.INPUT_TYPE)
inputs["NumDataPointsPerSet"] = []
inputs["NumDataPointsPerSet"].append(str(len(inputs["AppSize"])))
# Build up the arguments list for each invocation of the benchmark.
# This is done here, instead of in ccbench.py, because this is custom to each app.
app_args_list = []
for run_type in inputs["RunType"]:
for app_size in inputs["AppSize"]:
app_args_list.append(str(app_size) + " " \
+ str(inputs["NumIterations"][0]) + " " +str(run_type))
# 2. Execute the benchmark and write to the report file.
if (not ccbench.NORUN):
ccbench.runBenchmark(app_bin, app_args_list, inputs, input_variables,
report_filename)
# 3. Extract Data from the report file.
data = ccbench.readReportFile(report_filename, variables)
# 4. Plot the Data
#print data
if NOPLOT:
return
if PLOT_POSTER:
fig = plt.figure(figsize=(5, 3.5))
font = { #'family' : 'normal',
#'weight' : 'bold',
'size': 8
}
matplotlib.rc('font', **font)
fig.subplots_adjust(top=0.94,
bottom=0.14,
left=0.1,
right=0.96,
wspace=0,
hspace=0)
else:
fig = plt.figure(figsize=(9, 5.5))
fig.subplots_adjust(top=0.95,
bottom=0.12,
left=0.07,
right=0.97,
wspace=0,
hspace=0)
p1 = fig.add_subplot(1, 1, 1)
print "Plotting time..."
num_datapoints = int(data["NumDataPointsPerSet"][0])
# let's convert "appsizearg(#elm)" to "appsize(KB)"
for i in range(len(data["AppSize"])):
data["AppSize"][i] = str(float(data["AppSize"][i]) * 4 / 1024)
for i in range(len(data["AppSize"]) / num_datapoints):
srt_idx = i * num_datapoints
end_idx = (i + 1) * num_datapoints
p1.plot(data["AppSize"][srt_idx:end_idx],
data["Time"][srt_idx:end_idx],
linestyle='--',
marker='.')
p1.set_xscale('log')
p1.set_yscale('log')
plt.ylabel(data["TimeUnits"][0])
plt.xlabel('Array Size')
plt.ylim((1, 320))
xmin, xmax = plt.xlim()
plt.xlim((0.5, 1024 * 64))
# deal with ticks
xtick_range = [
1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 4096, 4096 * 2,
16384, 16384 * 2, 16384 * 4
]
xtick_names = [
'1 kB', '2 kB', '4 kB', '8 kB', '16 kB', '32 kB', '64 kB', '128 kB',
'256 kB', '512 kB', '1 MB', '2 MB', '4 MB', '8 MB', '16 MB', '32 MB',
'64 MB'
] #for KB
ytick_range = [1, 2, 4, 8, 16, 32, 64, 128, 256] # in ns / iteration
ytick_names = ['1', '2', '4', '8', '16', '32', '64', '128', '256']
if (xmax > 1024 * 65):
xtick_range = [
1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 4096, 4096 * 2,
16384, 16384 * 2, 16384 * 4, 1024 * 128
]
xtick_names = [
'1 kB', '2 kB', '4 kB', '8 kB', '16 kB', '32 kB', '64 kB',
'128 kB', '256 kB', '512 kB', '1 MB', '2 MB', '4 MB', '8 MB',
'16 MB', '32 MB', '64 MB', '128 MB'
] #for KB
plt.xlim((0.5, 1024 * 128))
if (xmax > 1024 * 128):
xtick_range = [
1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 4096, 4096 * 2,
16384, 16384 * 2, 16384 * 4, 1024 * 128, 1024 * 256
]
xtick_names = [
'1 kB', '2 kB', '4 kB', '8 kB', '16 kB', '32 kB', '64 kB',
'128 kB', '256 kB', '512 kB', '1 MB', '2 MB', '4 MB', '8 MB',
'16 MB', '32 MB', '64 MB', '128 MB', '256 MB'
] #for KB
plt.xlim((0.5, 1024 * 256))
p1.xaxis.set_major_locator(plt.NullLocator())
p1.xaxis.set_minor_locator(plt.NullLocator())
p1.yaxis.set_major_locator(plt.NullLocator())
p1.yaxis.set_minor_locator(plt.NullLocator())
plt.xticks(xtick_range, xtick_names, rotation='-30', size='small')
plt.yticks(ytick_range, ytick_names)
# annotate the graph with pretty cache size lines and info!
ylow = 160
yhigh = 200
ccprocstats.plotCacheSizeLines(plt, p1, ccbench.PROCESSOR, ylow, yhigh)
# customize figure title and other doodads based on the processor the test was run on
print " "
if (ccbench.PROCESSOR == "merom"):
outputAccessLatency(data, 8, "L1 ", 2.33)
outputAccessLatency(data, 64, "L2 ", 2.33)
outputAccessLatency(data, 16384, "Off-chip", 2.33)
if (ccbench.PROCESSOR == "ivybridge"):
outputAccessLatency(data, 8, "L1 ", 2.3)
outputAccessLatency(data, 128, "L2 ", 2.3)
outputAccessLatency(data, 3072, "L3 ", 2.3)
outputAccessLatency(data, 16384, "Off-chip", 2.3)
elif (ccbench.PROCESSOR == "cuda1"):
outputAccessLatency(data, 8, "L1 ", 2.4)
outputAccessLatency(data, 64, "L2 ", 2.4)
outputAccessLatency(data, 16384, "Off-chip", 2.4)
elif (ccbench.PROCESSOR == "tegra2"):
outputAccessLatency(data, 8, "L1 ", 0.4)
#umnown
outputAccessLatency(data, 64, "L2 ", 0.4)
outputAccessLatency(data, 16384, "Off-chip", 0.4)
elif (ccbench.PROCESSOR == "tilera"):
outputAccessLatency(data, 4, "L1 ", 0.7)
outputAccessLatency(data, 32, "L2 ", 0.7)
outputAccessLatency(data, 1024, "L3* ", 0.7)
outputAccessLatency(data, 16384, "Off-chip", 0.7)
elif (ccbench.PROCESSOR == "tilera-l3"): #unknown
outputAccessLatency(data, 4, "L1 ", 0.7)
outputAccessLatency(data, 32, "L2 ", 0.7)
outputAccessLatency(data, 1024, "L3 ", 0.7)
outputAccessLatency(data, 16384, "Off-chip", 0.7)
elif (ccbench.PROCESSOR == "arrandale"):
outputAccessLatency(data, 8, "L1 ", 3.0)
#unknwno
outputAccessLatency(data, 64, "L2 ", 3.0)
outputAccessLatency(data, 1024, "L3 ", 3.0)
outputAccessLatency(data, 16384, "Off-chip", 3.0)
elif (ccbench.PROCESSOR == "bloomfield"):
outputAccessLatency(data, 8, "L1 ", 3.4)
#unknown
outputAccessLatency(data, 64, "L2 ", 3.4)
outputAccessLatency(data, 1024, "L3 ", 3.4)
outputAccessLatency(data, 16384, "Off-chip", 3.4)
elif (ccbench.PROCESSOR == "emerald"):
outputAccessLatency(data, 8, "L1 ", 2.27)
outputAccessLatency(data, 64, "L2 ", 2.27)
outputAccessLatency(data, 1024, "L3 ", 2.27)
outputAccessLatency(data, 16384, "L3 ", 2.27)
outputAccessLatency(data, 128 * 1024, "Off-chip", 2.27)
elif (ccbench.PROCESSOR == "boxboro"
): #boxboro.millennium machine (westmere-ex)
outputAccessLatency(data, 8, "L1 ", 2.27)
outputAccessLatency(data, 64, "L2 ", 2.27)
outputAccessLatency(data, 1024, "L3 ", 2.27)
outputAccessLatency(data, 65536, "Off-chip", 2.27)
outputAccessLatency(data, 262144, "DRAM ", 2.27)
elif (ccbench.PROCESSOR == "bridge"):
outputAccessLatency(data, 8, "L1 ", 3.4)
outputAccessLatency(data, 64, "L2 ", 3.4)
outputAccessLatency(data, 1024, "L3 ", 3.4)
outputAccessLatency(data, 262144, "DRAM ", 3.4)
else:
plt.title("Cache Hierarchy" + r'', fontstyle='italic')
print " Unknown processor - cycle count is assuming a 1 GHz clock"
outputAccessLatency(data, 8, "", 1.0)
outputAccessLatency(data, 64, "", 1.0)
outputAccessLatency(data, 1024, "", 1.0)
outputAccessLatency(data, 16384, "", 1.0)
print " "
if (ccbench.PLOT_FILENAME == "none"):
filename = PLOT_DIR + ccbench.generatePlotFileName(APP)
else:
# Pull out the filename path from the full path.
# This allows us to pull out the requested filename from the path presented
# (since we always write reports to the report directory, etc.). However, it
# allows the user to use tab-completion to specify the exact reportfile he
# wants to use.
filename = PLOT_DIR + os.path.basename(ccbench.PLOT_FILENAME)
filename = os.path.splitext(filename)[0]
plt.savefig(filename)
print "Used report filename : " + report_filename
print "Finished Plotting, saved as file : " + filename + ".pdf"
def main():
# handle CLI options
ccbench.controller()
#handle default/cli args app
app_bin = BASE_DIR + APP
input_filename = BASE_DIR + DEFAULT_INPUT_NAME
report_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR)
# 1. Parse inputs.txt file.
if (not ccbench.NORUN):
inputs = ccbench.parseInputFile(input_filename, variables, ccbench.INPUT_TYPE)
inputs["NumDataPointsPerSet"] = []
inputs["NumDataPointsPerSet"].append(str(len(inputs["AppSize"])))
# Build up the arguments list for each invocation of the benchmark.
# This is done here, instead of in ccbench.py, because this is custom to each app.
app_args_list = []
for app_size in inputs["AppSize"]:
app_args_list.append(str(app_size) + " " + str(inputs["NumIterations"][0]))
# 2. Execute the benchmark and write to the report file.
if (not ccbench.NORUN):
ccbench.runBenchmark(app_bin, app_args_list, inputs, input_variables, report_filename)
# 3. Extract Data from the report file.
data = ccbench.readReportFile(report_filename, variables)
# 4. Plot the Data
#print data
if NOPLOT:
return
if PLOT_PPT:
font = {#'family' : 'normal',
#'weight' : 'bold',
'size' : 30}
matplotlib.rc('font', **font)
fig.subplots_adjust(top=0.90, bottom=0.25, left=0.18, right=0.97,wspace=0, hspace=0)
xtick_range = [1,32,256, 4096*2,16384*4]
xtick_names = ['1 kB','32 kB','256 kB','8 MB','64 MB'] #for KB
elif PLOT_POSTER:
fig = plt.figure(figsize=(5,3.5))
font = {#'family' : 'normal',
#'weight' : 'bold',
'size' : 8}
matplotlib.rc('font', **font)
fig.subplots_adjust(top=0.94, bottom=0.14, left=0.1, right=0.96,wspace=0, hspace=0)
else:
fig = plt.figure(figsize=(9,5.5))
fig.subplots_adjust(top=0.95, bottom=0.12, left=0.07, right=0.97,wspace=0, hspace=0)
fig.subplots_adjust(top=0.95, bottom=0.12, left=0.1, right=0.97,wspace=0, hspace=0)
p1 = fig.add_subplot(1,1,1)
print "Plotting time..."
num_datapoints = int(data["NumDataPointsPerSet"][0])
# let's convert "appsizearg(#elm)" to "appsize(KB)"
for i in range(len(data["AppSize"])):
data["AppSize"][i] = str(float(data["AppSize"][i]) * 4 / 1024)
for i in range(len(data["AppSize"])/num_datapoints):
srt_idx = i*num_datapoints
end_idx = (i+1)*num_datapoints
p1.plot(
data["AppSize"][srt_idx:end_idx],
data["Output"][srt_idx:end_idx],
linestyle='--',
marker='.'#,
# linewidth=2
)
p1.set_xscale('log')
p1.set_yscale('log')
plt.ylabel(data["Units"][0])
plt.xlabel('Array Size')
# plt.ylim((1, 50000))
if (ccbench.PROCESSOR == "tilera-l3"):
plt.ylim((100, 10000))
elif (ccbench.PROCESSOR == "tilera"):
plt.ylim((100, 10000))
else:
plt.ylim((1000, 100000))
plt.xlim((0.5, 16384*4))
if not PLOT_PPT:
# deal with ticks
xtick_range = [1,2,4,8,16,32,64, 128,256, 512,1024,2048,4096,4096*2, 16384,16384*2,16384*4]
xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB','32 MB','64 MB'] #for KB
# ytick_range = [1,10,100,,1000,10000]
# ytick_names = ['1','10','100','1e3','10e3']
p1.xaxis.set_major_locator( plt.NullLocator() )
p1.xaxis.set_minor_locator( plt.NullLocator() )
# p1.yaxis.set_major_locator( plt.NullLocator() )
# p1.yaxis.set_minor_locator( plt.NullLocator() )
plt.xticks(
xtick_range,
xtick_names,
rotation='-30',
size='small'
)
# plt.yticks(ytick_range,ytick_names)
(ymin, ymax) = plt.ylim()
print "ymax=%d log(ymax) = %f, " % (ymax, np.log(ymax))
# print "log(7) = %f, 2^3 = 8 (%f) " % (np.log(7), np.exp(2))
yvalue_top = np.exp2((np.log2(ymax) + np.log2(ymin))*0.42)
yvalue_bot = np.exp2((np.log2(ymax) + np.log2(ymin))*0.40)
# yvalue_top = ymax*0.95 #np.exp(np.log(ymax) + np.log(ymin)/(2))
# yvalue_bot = yvalue_top*0.95 #np.exp(np.log(ymax) + np.log(ymin)/(2))
ccprocstats.plotCacheSizeLines(plt, p1, ccbench.PROCESSOR, yvalue_bot, yvalue_top)
if (ccbench.PLOT_FILENAME == "none"):
filename = ccbench.generatePlotFileName(APP)
else:
filename = PLOT_DIR + os.path.basename(ccbench.PLOT_FILENAME)
filename = os.path.splitext(filename)[0]
plt.savefig(filename)
print "Used report filename : " + report_filename
print "Finished Plotting, saved as file : " + filename + ".pdf"
def main(args=None, report_dir=None):
global REPORT_DIR
global PLOT_DIR
# handle CLI options
if (report_dir != None):
REPORT_DIR = report_dir
PLOT_DIR = report_dir
ccbench.controller(args)
#handle default/cli args app
app_bin = BASE_DIR + APP
#input_filename = BASE_DIR + DEFAULT_INPUT_NAME
report_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR)
report_csv_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR, ".csv")
# 1. Parse inputs.txt file.
# Build up the arguments list for each invocation of the benchmark.
# This is done here, instead of in ccbench.py, because this is custom to each app.
app_args_list = []
if (ccbench.CONFIG != 'none'):
ccbench.parseConfigFile(APP)
app_args_list.append(ccbench.SIZE + " " + ccbench.MIN_RUN_TIME)#ccbench.ITERATIONS)
# 2. Execute the benchmark and write to the report file.
ccbench.runBenchmark(app_bin, app_args_list, report_filename)
# 3. Extract Data from the report file.
data = ccbench.readReportFile(report_filename, variables)
# 4. Plot the Data
#print data
if (not ccbench.NOPLOT):
if PLOT_POSTER:
fig = plt.figure(figsize=(5,3.5))
font = {#'family' : 'normal',
#'weight' : 'bold',
'size' : 8}
matplotlib.rc('font', **font)
fig.subplots_adjust(top=0.94, bottom=0.14, left=0.1, right=0.96,wspace=0, hspace=0)
else:
fig = plt.figure(figsize=(9,5.5))
fig.subplots_adjust(top=0.95, bottom=0.12, left=0.07, right=0.97,wspace=0, hspace=0)
p1 = fig.add_subplot(1,1,1)
print("Plotting time...")
sets = collections.OrderedDict()
if (ccbench.NOPLOT):
csv_file = open(report_csv_filename, "a+")
header = "totalTime"
data_list = []
for i in range(len(data["thread"])):
thread = data["thread"][i]
if thread in sets:
sets[thread][0].append(data["totalTime"][i])
sets[thread][1].append(data["rate"][i])
else:
sets[thread] = [[data["totalTime"][i]],[data["rate"][i]]]
for key, value in sets.items():
if (ccbench.NOPLOT):
header += ",{}".format(key)
for i in range(len(value[0])):
data_list.append(value[0][i] + "," + (","*int(key)) + value[1][i] + ("," *(len(sets)-1 - int(key)))+"\n")
else:
plot_label = 'Thread ' + key
p1.plot(
[float(i) for i in value[0]],
[float(i) for i in value[1]],
label= plot_label
)
if (ccbench.NOPLOT):
csv_file.write(header+"\n")
csv_file.writelines(data_list)
csv_file.close()
print("Saved data in CSV -> " + report_csv_filename)
else:
plt.legend(loc='upper left')
plt.ylabel("rate (MB/s)")
plt.xlabel('Time (s)')
#ytick_range = [1,2,4,8,16,32,64,128,256] # in ns / iteration
#ytick_names = ['1','2','4','8','16','32','64','128','256']
#p1.yaxis.set_major_locator( plt.NullLocator() )
#p1.yaxis.set_minor_locator( plt.NullLocator() )
#plt.yticks(ytick_range,ytick_names)
if (ccbench.PLOT_FILENAME == "none"):
filename = PLOT_DIR + ccbench.generatePlotFileName(APP)
else:
# Pull out the filename path from the full path.
# This allows us to pull out the requested filename from the path presented
# (since we always write reports to the report directory, etc.). However, it
# allows the user to use tab-completion to specify the exact reportfile he
# wants to use.
filename = PLOT_DIR + os.path.basename(ccbench.PLOT_FILENAME)
filename = os.path.splitext(filename)[0]
plt.savefig(filename)
print( "Used report filename : " + report_filename)
print("Finished Plotting, saved as file : " + filename + ".pdf")
def main():
# handle CLI options
ccbench.controller()
#handle default/cli args app
app_bin = BASE_DIR + APP
input_filename = BASE_DIR + DEFAULT_INPUT_NAME
report_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR)
# 1. Parse inputs.txt file.
if (not ccbench.NORUN):
inputs = ccbench.parseInputFile(input_filename, variables, ccbench.INPUT_TYPE)
inputs["NumDataPointsPerSet"] = []
inputs["NumDataPointsPerSet"].append(str(len(inputs["AppSize"])))
# Build up the arguments list for each invocation of the benchmark.
# This is done here, instead of in ccbench.py, because this is custom to each app.
app_args_list = []
for run_type in inputs["RunType"]:
for app_size in inputs["AppSize"]:
app_args_list.append(str(app_size) + " " \
+ str(inputs["NumIterations"][0]) + " " +str(run_type))
# 2. Execute the benchmark and write to the report file.
if (not ccbench.NORUN):
ccbench.runBenchmark(app_bin, app_args_list, inputs, input_variables, report_filename)
# 3. Extract Data from the report file.
data = ccbench.readReportFile(report_filename, variables)
# 4. Plot the Data
#print data
if NOPLOT:
return
if PLOT_POSTER:
fig = plt.figure(figsize=(5,3.5))
font = {#'family' : 'normal',
#'weight' : 'bold',
'size' : 8}
matplotlib.rc('font', **font)
fig.subplots_adjust(top=0.94, bottom=0.14, left=0.1, right=0.96,wspace=0, hspace=0)
else:
fig = plt.figure(figsize=(9,5.5))
fig.subplots_adjust(top=0.95, bottom=0.12, left=0.07, right=0.97,wspace=0, hspace=0)
p1 = fig.add_subplot(1,1,1)
print "Plotting time..."
num_datapoints = int(data["NumDataPointsPerSet"][0])
# let's convert "appsizearg(#elm)" to "appsize(KB)"
for i in range(len(data["AppSize"])):
data["AppSize"][i] = str(float(data["AppSize"][i]) * 4 / 1024)
for i in range(len(data["AppSize"])/num_datapoints):
srt_idx = i*num_datapoints
end_idx = (i+1)*num_datapoints
p1.plot(
data["AppSize"][srt_idx:end_idx],
data["Time"][srt_idx:end_idx],
linestyle='--',
marker='.'
)
p1.set_xscale('log')
p1.set_yscale('log')
plt.ylabel(data["TimeUnits"][0])
plt.xlabel('Array Size')
plt.ylim((1, 320))
xmin,xmax=plt.xlim()
plt.xlim((0.5, 1024*64))
# deal with ticks
xtick_range = [1,2,4,8,16,32,64, 128,256, 512,1024,2048,4096,4096*2, 16384,16384*2,16384*4]
xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB','32 MB','64 MB'] #for KB
ytick_range = [1,2,4,8,16,32,64,128,256] # in ns / iteration
ytick_names = ['1','2','4','8','16','32','64','128','256']
if (xmax > 1024*65):
xtick_range = [1,2,4,8,16,32,64, 128,256, 512,1024,2048,4096,4096*2, 16384,16384*2,16384*4,1024*128]
xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB','32 MB','64 MB','128 MB'] #for KB
plt.xlim((0.5,1024*128))
if (xmax > 1024*128):
xtick_range = [1,2,4,8,16,32,64, 128,256, 512,1024,2048,4096,4096*2, 16384,16384*2,16384*4,1024*128,1024*256]
xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB','32 MB','64 MB','128 MB','256 MB'] #for KB
plt.xlim((0.5,1024*256))
p1.xaxis.set_major_locator( plt.NullLocator() )
p1.xaxis.set_minor_locator( plt.NullLocator() )
p1.yaxis.set_major_locator( plt.NullLocator() )
p1.yaxis.set_minor_locator( plt.NullLocator() )
plt.xticks(
xtick_range,
xtick_names,
rotation='-30',
size='small'
)
plt.yticks(ytick_range,ytick_names)
# annotate the graph with pretty cache size lines and info!
ylow = 160
yhigh = 200
ccprocstats.plotCacheSizeLines(plt, p1, ccbench.PROCESSOR, ylow, yhigh)
# customize figure title and other doodads based on the processor the test was run on
print " ";
if (ccbench.PROCESSOR == "merom"):
outputAccessLatency(data, 8, "L1 ", 2.33);
outputAccessLatency(data, 64, "L2 ", 2.33);
outputAccessLatency(data, 16384, "Off-chip", 2.33);
if (ccbench.PROCESSOR == "ivybridge"):
outputAccessLatency(data, 8, "L1 ", 2.3);
outputAccessLatency(data, 128, "L2 ", 2.3);
outputAccessLatency(data, 3072, "L3 ", 2.3);
outputAccessLatency(data, 16384, "Off-chip", 2.3);
elif (ccbench.PROCESSOR == "cuda1"):
outputAccessLatency(data, 8, "L1 ", 2.4);
outputAccessLatency(data, 64, "L2 ", 2.4);
outputAccessLatency(data, 16384, "Off-chip", 2.4);
elif (ccbench.PROCESSOR == "tegra2"):
outputAccessLatency(data, 8, "L1 ", 0.4); #umnown
outputAccessLatency(data, 64, "L2 ", 0.4);
outputAccessLatency(data, 16384, "Off-chip", 0.4);
elif (ccbench.PROCESSOR == "tilera"):
outputAccessLatency(data, 4, "L1 ", 0.7);
outputAccessLatency(data, 32, "L2 ", 0.7);
outputAccessLatency(data, 1024, "L3* ", 0.7);
outputAccessLatency(data, 16384, "Off-chip", 0.7);
elif (ccbench.PROCESSOR == "tilera-l3"): #unknown
outputAccessLatency(data, 4, "L1 ", 0.7);
outputAccessLatency(data, 32, "L2 ", 0.7);
outputAccessLatency(data, 1024, "L3 ", 0.7);
outputAccessLatency(data, 16384, "Off-chip", 0.7);
elif (ccbench.PROCESSOR == "arrandale"):
outputAccessLatency(data, 8, "L1 ", 3.0); #unknwno
outputAccessLatency(data, 64, "L2 ", 3.0);
outputAccessLatency(data, 1024, "L3 ", 3.0);
outputAccessLatency(data, 16384, "Off-chip", 3.0);
elif (ccbench.PROCESSOR == "bloomfield"):
outputAccessLatency(data, 8, "L1 ", 3.4); #unknown
outputAccessLatency(data, 64, "L2 ", 3.4);
outputAccessLatency(data, 1024, "L3 ", 3.4);
outputAccessLatency(data, 16384, "Off-chip", 3.4);
elif (ccbench.PROCESSOR == "emerald"):
outputAccessLatency(data, 8, "L1 ", 2.27);
outputAccessLatency(data, 64, "L2 ", 2.27);
outputAccessLatency(data, 1024, "L3 ", 2.27);
outputAccessLatency(data, 16384, "L3 ", 2.27);
outputAccessLatency(data, 128*1024, "Off-chip", 2.27);
elif (ccbench.PROCESSOR == "boxboro"): #boxboro.millennium machine (westmere-ex)
outputAccessLatency(data, 8, "L1 ", 2.27);
outputAccessLatency(data, 64, "L2 ", 2.27);
outputAccessLatency(data, 1024, "L3 ", 2.27);
outputAccessLatency(data, 65536, "Off-chip", 2.27);
outputAccessLatency(data,262144, "DRAM ", 2.27);
elif (ccbench.PROCESSOR == "bridge"):
outputAccessLatency(data, 8, "L1 ", 3.4);
outputAccessLatency(data, 64, "L2 ", 3.4);
outputAccessLatency(data, 1024, "L3 ", 3.4);
outputAccessLatency(data,262144, "DRAM ", 3.4);
else:
plt.title("Cache Hierarchy" + r'', fontstyle='italic')
print " Unknown processor - cycle count is assuming a 1 GHz clock"
outputAccessLatency(data, 8, "", 1.0);
outputAccessLatency(data, 64, "", 1.0);
outputAccessLatency(data, 1024, "", 1.0);
outputAccessLatency(data, 16384, "", 1.0);
print " ";
if (ccbench.PLOT_FILENAME == "none"):
filename = PLOT_DIR + ccbench.generatePlotFileName(APP)
else:
# Pull out the filename path from the full path.
# This allows us to pull out the requested filename from the path presented
# (since we always write reports to the report directory, etc.). However, it
# allows the user to use tab-completion to specify the exact reportfile he
# wants to use.
filename = PLOT_DIR + os.path.basename(ccbench.PLOT_FILENAME)
filename = os.path.splitext(filename)[0]
plt.savefig(filename)
print "Used report filename : " + report_filename
print "Finished Plotting, saved as file : " + filename + ".pdf"
def main():
ccbench.controller() # handle CLI options
#handle default/cli args app
app_bin = BASE_DIR + APP
input_filename = BASE_DIR + DEFAULT_INPUT_NAME
report_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR)
# 1. Parse inputs.txt file
if (not ccbench.NORUN):
inputs = ccbench.parseInputFile(input_filename, input_variables, ccbench.INPUT_TYPE)
NumDataPointsPerSet = 0
# Build up the arguments list for each invocation of the benchmark.
# This is done here, instead of in ccbench.py, because this is custom to each app.
app_args_list = []
for num_threads in inputs["NumThreads"]:
for num_requests in inputs["NumRequests"]:
for app_size in inputs["AppSize"]:
NumDataPointsPerSet += num_threads #each thread spawns a new entry in band_req_mc!
app_args_list.append(str(num_threads) + " " + str(num_requests) + " " + str(app_size) \
+ " " + str(inputs["NumIterations"][0]))
inputs["NumDataPointsPerSet"] = []
inputs["NumDataPointsPerSet"].append(str(NumDataPointsPerSet))
# 2. Execute the benchmark and read the report file
if (not ccbench.NORUN):
ccbench.runBenchmark(app_bin, app_args_list, inputs, input_variables, report_filename)
# 3. Extract Data
data = ccbench.readReportFile(report_filename, variables)
inputs = ccbench.parseReportFileForInputs(report_filename, input_variables)
# 4. Plot the Data
#print data
if NOPLOT:
return
fig = plt.figure(figsize=(9,5.5))
p2 = fig.add_subplot(1,2,2)
p1 = fig.add_subplot(1,2,1)
print "Plotting time..."
num_datapoints = int(data["NumDataPointsPerSet"][0])
# let's convert "appsizearg(#elm)" to "appsize(KB)"
for i in range(len(data["AppSize"])):
data["AppSize"][i] = str(float(data["AppSize"][i]) * 4 / 1024)
# deal with ticks
# xtick_range = [1,2,4,8,16,32,64,128,256,512,1024,2048,4096,4096*2,16384] #for KB
# xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB'] #for KB
xtick_range = [1,4,16,64,256,1024,4096,16384] #for KB
xtick_names = ['1 kB','4 kB','16 kB','64 kB','256 kB','1 MB','4 MB','16 MB']
xmin,xmax = plt.xlim()
print "xmax = %d" % (xmax)
# if (xmax >= 1024*32):
# xtick_range = [1,2,4,8,16,32,64, 128,256, 512,1024,2048,4096,4096*2, 16384,16384*2,16384*4,1024*128]
# xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB','32 MB','64 MB','128 MB'] #for KB
xtick_range = [1,4,16,64,256,1024,4096,16384, 1024*64] #for KB
xtick_names = ['1 kB','4 kB','16 kB','64 kB','256 kB','1 MB','4 MB','16 MB', '64 MB']
plt.xlim((0.5,1024*128))
# fig.subplots_adjust(top=0.95, bottom=0.12, left=0.07, right=0.90,wspace=0, hspace=0)
fig.subplots_adjust(top=0.95, bottom=0.12, left=0.07, right=0.90,wspace=0.13, hspace=0)
c_counter = 0
colors =('b','g','r','c','m','y','k','b','g','r','c','m')
line_styles=('-.',':','-.',':')
for num_threads in inputs["NumThreads"]:
#x_array = [int(s) for s in array ]
# print "NumThreads, graphing NumThreads: " + str(num_threads)
l_counter = 0
color = colors [c_counter % len(colors)]
c_counter +=1
# plot a line for each tid in th eexperiment NumThreads
for num_req in inputs["NumRequests"]:
line_style = line_styles[l_counter % len(line_styles)]
l_counter += 1
for tid in range(num_threads):
x_array = []
band_array = []
aggr_array = []
for idx in range(len(data["AppSize"])):
# print " looking at idx: " + str(idx) + " in data[apsize]"
if (int(data["ThreadID"][idx]) == int(tid)) and (int(data["NumThreads"][idx]) == num_threads) and (int(data["NumRequests"][idx]) == num_req):
# print " appending " + data["AppSize"][idx] + " For ThreadID: " + data["ThreadID"][idx]
x_array.append(data["AppSize"][idx])
aggr_array.append(data["AggregateBandwidth"][idx])
band_array.append(data["Bandwidth"][idx])
p1.plot(
x_array,
band_array,
# linestyle="--",
linestyle=line_style,
# linestyle=" ",
marker='.',
color = color
)
p2.plot(
x_array,
aggr_array,
# linestyle="--",
linestyle=line_style,
# linestyle=" ",
marker='.',
color = color
)
p1.set_xscale('log')
p2.set_xscale('log')
plt.ylabel(data["BandwidthUnits"][0])
plt.xlabel('Per Thread Working Set')
ymin, ymax = plt.ylim()
plt.ylim((0.0, ymax))
plt.xlim((0.5, 16384))
p1.xaxis.set_major_locator( plt.NullLocator() )
p1.xaxis.set_minor_locator( plt.NullLocator() )
p2.xaxis.set_major_locator( plt.NullLocator() )
p2.xaxis.set_minor_locator( plt.NullLocator() )
plt.xticks(
xtick_range,
xtick_names,
rotation='-30',
size='small'
)
p2 = fig.add_subplot(1,2,2)
plt.xticks(
xtick_range,
xtick_names,
rotation='-30',
size='small'
)
# resize the per thread bandwidth...(to match aggregate bandwidth)
#p2 = fig.add_subplot(1,2,2)
#(ylow,yhigh) = plt.ylim()
#p1 = fig.add_subplot(1,2,1)
#plt.ylim((ylow,yhigh))
# plot processor-specific info
p1 = fig.add_subplot(1,2,1)
(ylow,yhigh) = plt.ylim()
yhigh = 0.95*yhigh
ylow = 0.95*yhigh
ccprocstats.plotCacheSizeLines(plt, p1, ccbench.PROCESSOR, ylow, yhigh)
p2 = fig.add_subplot(1,2,2)
plt.xlabel('Per Thread Working Set')
(ylow,yhigh) = plt.ylim()
yhigh = 0.95*yhigh
ylow = 0.95*yhigh
ccprocstats.plotCacheSizeLines(plt, p2, ccbench.PROCESSOR, ylow, yhigh)
p2 = fig.add_subplot(1,2,2)
plt.title("Aggregate Bandwidth" + r'', fontstyle='italic')
p1 = fig.add_subplot(1,2,1)
plt.title("Per Thread Bandwidth" + r'', fontstyle='italic')
# legend
colors =('b','g','r','c','m','y','k','b','g','r','c','m')
legend_sz = len(inputs["NumThreads"])
lines = []
for i in (range(legend_sz)):
lines.append(plt.Line2D([0,10], [0,10], linewidth=3, color=colors[legend_sz-1-i], linestyle='-'))
args = range(legend_sz)
for i in (range(legend_sz)):
args[legend_sz - 1 - i] = str(inputs["NumThreads"][i]) + " Threads"
# args[legend_sz - 1 - i] = "{Thds:" + str(inputs["NumThreads"][i]) + "}" #+ ", Reqs:" + input["NumRequests"][((i)*num_datapoints)] + "}"
p2 = fig.add_subplot(1,2,2)
plt.legend(lines, args, 'best', title="Num of Threads", bbox_to_anchor=(0.70, 0.9))
(ylow,yhigh) = plt.ylim()
(xmin,xmax) = plt.xlim()
p2.text(xmax, 0.9*yhigh, "%d requests / thread" % (inputs["NumRequests"][0]), horizontalalignment='center',verticalalignment='center', size='x-small')
if (ccbench.PLOT_FILENAME == "none"):
filename = PLOT_DIR + ccbench.generatePlotFileName(APP)
else:
# Pull out the filename path from the full path.
# This allows us to pull out the requested filename from the path presented
# (since we always write reports to the report directory, etc.). However, it
# allows the user to use tab-completion to specify the exact reportfile he
# wants to use.
filename = PLOT_DIR + os.path.basename(ccbench.PLOT_FILENAME)
filename = os.path.splitext(filename)[0]
plt.savefig(filename)
print "Used report filename : " + report_filename
print "Finished Plotting, saved as file : " + filename + ".pdf"
def main():
# handle CLI options
ccbench.controller()
#handle default/cli args app
app_bin = BASE_DIR + APP
input_filename = BASE_DIR + DEFAULT_INPUT_NAME
report_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR)
# 1. Parse inputs.txt file.
if (not ccbench.NORUN):
inputs = ccbench.parseInputFile(input_filename, variables,
ccbench.INPUT_TYPE)
inputs["NumDataPointsPerSet"] = []
inputs["NumDataPointsPerSet"].append(str(len(inputs["AppSize"])))
# Build up the arguments list for each invocation of the benchmark.
# This is done here, instead of in ccbench.py, because this is custom to each app.
app_args_list = []
for app_size in inputs["AppSize"]:
app_args_list.append(
str(app_size) + " " + str(inputs["NumIterations"][0]))
# 2. Execute the benchmark and write to the report file.
if (not ccbench.NORUN):
ccbench.runBenchmark(app_bin, app_args_list, inputs, input_variables,
report_filename)
# 3. Extract Data from the report file.
data = ccbench.readReportFile(report_filename, variables)
# 4. Plot the Data
#print data
if NOPLOT:
return
if PLOT_PPT:
font = { #'family' : 'normal',
#'weight' : 'bold',
'size': 30
}
matplotlib.rc('font', **font)
fig.subplots_adjust(top=0.90,
bottom=0.25,
left=0.18,
right=0.97,
wspace=0,
hspace=0)
xtick_range = [1, 32, 256, 4096 * 2, 16384 * 4]
xtick_names = ['1 kB', '32 kB', '256 kB', '8 MB', '64 MB'] #for KB
elif PLOT_POSTER:
fig = plt.figure(figsize=(5, 3.5))
font = { #'family' : 'normal',
#'weight' : 'bold',
'size': 8
}
matplotlib.rc('font', **font)
fig.subplots_adjust(top=0.94,
bottom=0.14,
left=0.1,
right=0.96,
wspace=0,
hspace=0)
else:
fig = plt.figure(figsize=(9, 5.5))
fig.subplots_adjust(top=0.95,
bottom=0.12,
left=0.07,
right=0.97,
wspace=0,
hspace=0)
fig.subplots_adjust(top=0.95,
bottom=0.12,
left=0.1,
right=0.97,
wspace=0,
hspace=0)
p1 = fig.add_subplot(1, 1, 1)
print "Plotting time..."
num_datapoints = int(data["NumDataPointsPerSet"][0])
# let's convert "appsizearg(#elm)" to "appsize(KB)"
for i in range(len(data["AppSize"])):
data["AppSize"][i] = str(float(data["AppSize"][i]) * 4 / 1024)
for i in range(len(data["AppSize"]) / num_datapoints):
srt_idx = i * num_datapoints
end_idx = (i + 1) * num_datapoints
p1.plot(
data["AppSize"][srt_idx:end_idx],
data["Output"][srt_idx:end_idx],
linestyle='--',
marker='.' #,
# linewidth=2
)
p1.set_xscale('log')
p1.set_yscale('log')
plt.ylabel(data["Units"][0])
plt.xlabel('Array Size')
# plt.ylim((1, 50000))
if (ccbench.PROCESSOR == "tilera-l3"):
plt.ylim((100, 10000))
elif (ccbench.PROCESSOR == "tilera"):
plt.ylim((100, 10000))
else:
plt.ylim((1000, 100000))
plt.xlim((0.5, 16384 * 4))
if not PLOT_PPT:
# deal with ticks
xtick_range = [
1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 4096, 4096 * 2,
16384, 16384 * 2, 16384 * 4
]
xtick_names = [
'1 kB', '2 kB', '4 kB', '8 kB', '16 kB', '32 kB', '64 kB',
'128 kB', '256 kB', '512 kB', '1 MB', '2 MB', '4 MB', '8 MB',
'16 MB', '32 MB', '64 MB'
] #for KB
# ytick_range = [1,10,100,,1000,10000]
# ytick_names = ['1','10','100','1e3','10e3']
p1.xaxis.set_major_locator(plt.NullLocator())
p1.xaxis.set_minor_locator(plt.NullLocator())
# p1.yaxis.set_major_locator( plt.NullLocator() )
# p1.yaxis.set_minor_locator( plt.NullLocator() )
plt.xticks(xtick_range, xtick_names, rotation='-30', size='small')
# plt.yticks(ytick_range,ytick_names)
(ymin, ymax) = plt.ylim()
print "ymax=%d log(ymax) = %f, " % (ymax, np.log(ymax))
# print "log(7) = %f, 2^3 = 8 (%f) " % (np.log(7), np.exp(2))
yvalue_top = np.exp2((np.log2(ymax) + np.log2(ymin)) * 0.42)
yvalue_bot = np.exp2((np.log2(ymax) + np.log2(ymin)) * 0.40)
# yvalue_top = ymax*0.95 #np.exp(np.log(ymax) + np.log(ymin)/(2))
# yvalue_bot = yvalue_top*0.95 #np.exp(np.log(ymax) + np.log(ymin)/(2))
ccprocstats.plotCacheSizeLines(plt, p1, ccbench.PROCESSOR, yvalue_bot,
yvalue_top)
if (ccbench.PLOT_FILENAME == "none"):
filename = ccbench.generatePlotFileName(APP)
else:
filename = PLOT_DIR + os.path.basename(ccbench.PLOT_FILENAME)
filename = os.path.splitext(filename)[0]
plt.savefig(filename)
print "Used report filename : " + report_filename
print "Finished Plotting, saved as file : " + filename + ".pdf"
def main():
ccbench.controller() # handle CLI options
#handle default/cli args app
app_bin = BASE_DIR + APP
input_filename = BASE_DIR + DEFAULT_INPUT_NAME
report_filename = REPORT_DIR + ccbench.getReportFileName(APP, REPORT_DIR)
# 1. Parse inputs.txt file
if (not ccbench.NORUN):
inputs = ccbench.parseInputFile(input_filename, input_variables, ccbench.INPUT_TYPE)
inputs["NumDataPointsPerSet"] = []
inputs["NumDataPointsPerSet"].append(str(len(inputs["AppSize"])))
# Build up the arguments list for each invocation of the benchmark.
# This is done here, instead of in ccbench.py, because this is custom to each app.
app_args_list = []
for num_requests in inputs["NumRequests"]:
for app_size in inputs["AppSize"]:
app_args_list.append(str(num_requests) + " " + str(app_size) \
+ " " + str(inputs["NumIterations"][0]))
# 2. Execute the benchmark and read the report file
if (not ccbench.NORUN):
ccbench.runBenchmark(app_bin, app_args_list, inputs, input_variables, report_filename)
# 3. Extract Data
data = ccbench.readReportFile(report_filename, variables)
# 4. Plot the Data
#print data
if NOPLOT:
return
if PLOT_POSTER:
fig = plt.figure(figsize=(5,3.5))
font = {#'family' : 'normal',
#'weight' : 'bold',
'size' : 8}
matplotlib.rc('font', **font)
fig.subplots_adjust(top=0.94, bottom=0.14, left=0.09, right=0.91,wspace=0, hspace=0)
else:
fig = plt.figure(figsize=(9,5.5))
fig.subplots_adjust(top=0.95, bottom=0.12, left=0.07, right=0.90,wspace=0, hspace=0)
p1 = fig.add_subplot(1,1,1)
print "Plotting time..."
num_datapoints = int(data["NumDataPointsPerSet"][0])
# let's convert "appsizearg(#elm)" to "appsize(KB)"
for i in range(len(data["AppSize"])):
data["AppSize"][i] = str(float(data["AppSize"][i]) * 4 / 1024)
# deal with ticks
xtick_range = [1,2,4,8,16,32,64,128,256,512,1024,2048,4096,4096*2,16384] #for KB
xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB'] #for KB
xmin,xmax = plt.xlim()
# print "xmax = %d" % (xmax)
# if (xmax >= 1024*32):
xtick_range = [1,2,4,8,16,32,64, 128,256, 512,1024,2048,4096,4096*2, 16384,16384*2,16384*4,1024*128]
xtick_names = ['1 kB','2 kB','4 kB','8 kB','16 kB','32 kB','64 kB','128 kB','256 kB','512 kB','1 MB','2 MB','4 MB','8 MB','16 MB','32 MB','64 MB','128 MB'] #for KB
plt.xlim((0.5,1024*128))
for i in range(len(data["AppSize"])/num_datapoints):
srt_idx = i*num_datapoints
end_idx = (i+1)*num_datapoints
p1.plot(
data["AppSize"][srt_idx:end_idx-1],
data["Bandwidth"][srt_idx:end_idx-1],
linestyle='--',
marker='.'
)
p1.set_xscale('log')
plt.ylabel(data["BandwidthUnits"][0])
plt.xlabel('Array Size')
ymin, ymax = plt.ylim()
print "ymax = %f" % ymax
if (ccbench.PROCESSOR == "tegra2" or ccbench.ARCHITECTURE == "arm" or ccbench.ARCHITECTURE == "riscv"):
plt.ylim((0.0, ymax))
else:
plt.ylim((0.0, 2.5e9))
plt.xlim((0.5, 16384))
p1.xaxis.set_major_locator( plt.NullLocator() )
p1.xaxis.set_minor_locator( plt.NullLocator() )
plt.xticks(
xtick_range,
xtick_names,
rotation='-30',
size='small'
)
# figure out y location of text labels normally you can use normalize
# coords, except i want to specify the x location exactly :/
ylow = 0
for datum in data["Bandwidth"]:
if (ylow < 1.02*float(datum)):
ylow = 1.02*float(datum)
(ylow,yhigh) = plt.ylim()
yhigh = 0.95*yhigh
ylow = 0.95*yhigh
ccprocstats.plotCacheSizeLines(plt, p1, ccbench.PROCESSOR, ylow, yhigh)
# legend
colors =('b','g','r','c','m','y','k','b','g','r','c','m')
legend_sz = len(data["NumRequests"])/num_datapoints
lines = []
#for i in reversed(range(legend_sz)):
for i in (range(legend_sz)):
lines.append(plt.Line2D([0,10], [0,10], linewidth=3, color=colors[legend_sz-1-i]))
args = range(legend_sz)
for i in (range(legend_sz)):
args[legend_sz - 1 - i] = data["NumRequests"][((i)*num_datapoints)]
#legend_font= FontProperties()
#legend_font.set_size('medium')
#plt.legend(lines, args, 'best', title="Num of\nRequests", prop=legend_font)
plt.legend(lines, args, 'best', title="Num of\nRequests", bbox_to_anchor=(1.12, 0.9))
if (ccbench.PLOT_FILENAME == "none"):
filename = PLOT_DIR + ccbench.generatePlotFileName(APP)
else:
# Pull out the filename path from the full path.
# This allows us to pull out the requested filename from the path presented
# (since we always write reports to the report directory, etc.). However, it
# allows the user to use tab-completion to specify the exact reportfile he
# wants to use.
filename = PLOT_DIR + os.path.basename(ccbench.PLOT_FILENAME)
filename = os.path.splitext(filename)[0]
plt.savefig(filename)
print "Used report filename : " + report_filename
print "Finished Plotting, saved as file : " + filename + ".pdf"