#!/s/std/bin/python
import sys, string, os, glob, re, mfgraph
GEMS = "/u/k/i/kidd/research/GEMS/GEMS"
results_dir = GEMS + "/results/"
#results_dir = "../results"
make_excel_files = 1
def get_int_stat(file, stat):
grep_lines = mfgraph.grep(file, stat)
line = string.split(grep_lines[0])
return int(line[1])
def get_int_param(file, param):
grep_lines = mfgraph.grep(file, param)
line = string.split(grep_lines[0])
return int(line[1])
def get_float_stat(file, stat):
grep_lines = mfgraph.grep(file, stat)
line = string.split(grep_lines[0])
return int(line[1])
def get_runtime(benchmark):
data = []
files = glob.glob(results_dir + "/" + benchmark + "/*.stats")
for file in files:
procs = get_int_stat(file, "g_NUM_NODES")
cycles = get_int_stat(file, "Ruby_cycles")
#print "%dp:\t%d" % (procs, cycles)
data.append((procs, cycles))
return data
def make_microbench_line(jgraphs, name, runs, bw, protocol_map, label):
xlabel = "Processors"
ylabel = "Run Time"
#proc_values = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
# 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
# 21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
# 31]
#proc_values = [1, 2, 3, 4, 5, 6, 7]
proc_values = [1, 2, 4, 8, 16, 32]
read_set = None
data = []
for run in runs:
#print run
protocol = protocol_map[run[2]]
line = [run[0]]
for procs in proc_values:
#print procs
lst = []
#read_set_str = "%s" % read_set
glob_str = "%s/%s/%s-%dp-*%s-*%d-*.stats" % (results_dir, run[1], run[1], procs, protocol, bw)
files = glob.glob(glob_str)
if files == []:
#print "No files match: %s" % glob_str
#exit
continue
for file in files:
print file
ruby_cycles = get_float_stat(file, "Ruby_cycles")/1000000.0
#divide by procs?
print "ruby_cycles: %f" % ruby_cycles
lst.append(ruby_cycles)
cycles = mfgraph.mean(lst)
#print lst
conf = mfgraph.confidence_interval_95_percent(lst)
#print "95 conf: %f" % conf
line.append([procs, cycles, cycles - conf, cycles + conf])
data.append(line)
print data
jgraphs.append(mfgraph.line_graph(data,
title = name,
ylabel = "Execution Time (in millions of cycles)",
xlabel = "Threads",
xsize = 4.5,
ysize = 8.0,
line_thickness = 2.0,
legend_x = "90",
marktype = ["circle", "box", "triangle", "diamond"],
#marksize = [0.4, 0.4, 0.4, 0.5],
))
graph_out = mfgraph.line_graph(data,
title = "",
ylabel = "Execution Time (in millions of cycles)",
#ymax = 1.50,
ymin = 0,
xsize = 2.5,
ysize = 1.778,
line_thickness = 2.0,
marktype = ["circle", "box", "triangle", "diamond"],
marksize = [0.2, 0.3, 0.3, 0.4],
title_fontsize = "12",
label_fontsize = "8",
legend_fontsize = "9",
legend_x = "70",
colors = ["0 0 0",
".6 .6 .6",
".2 .2 .2",
".8 .8 .8",
".4 .4 .4"]
)
mfgraph.make_eps(graph_out, "%s_%s_line" % (name, label), "xref_figures")
def make_microbench_speedup_line(jgraphs, name, runs, bw, protocol_map, label):
xlabel = "Processors"
ylabel = "Run Time"
proc_values = [1, 2, 4, 8, 16, 32]
read_set = None
data = []
for run in runs:
#print run
protocol = protocol_map[run[2]]
line = [run[0]]
base_cycles = 0.0
for procs in proc_values:
#print procs
lst = []
#read_set_str = "%s" % read_set
glob_str = "%s/%s/%s-%dp-*%s-%d-*.stats" % (results_dir, run[1], run[1], procs, protocol, bw)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
#exit
continue
for file in files:
#print file
ruby_cycles = get_float_stat(file, "Ruby_cycles")/1000000.0
#divide by procs?
#print "ruby_cycles: %f" % ruby_cycles
lst.append(ruby_cycles)
cycles = mfgraph.mean(lst)
conf = mfgraph.confidence_interval_95_percent(lst)
#print "95 conf: %f" % conf
if procs == 1:
base_cycles = cycles
#print "base_cycles is: %f" % base_cycles
line.append([procs, base_cycles/cycles, base_cycles/(cycles - conf), base_cycles/(cycles + conf)])
data.append(line)
#linear = ["Linear"]
#for p in proc_values:
# linear.append([p, p, p, p])
#data.append(linear)
#print data
jgraphs.append(mfgraph.line_graph(data,
title = name,
ylabel = "Speedup",
xlabel = "Threads",
xsize = 4.5,
ysize = 6.0,
line_thickness = 2.0,
legend_x = "90",
marktype = ["circle", "box", "triangle", "diamond"],
#marksize = [0.4, 0.4, 0.4, 0.5],
))
graph_out = mfgraph.line_graph(data,
title = "",
ylabel = "Speedup",
xlabel = "Threads",
ymin = 0,
xsize = 2.5,
ysize = 1.778,
line_thickness = 2.0,
marktype = ["circle", "box", "triangle", "diamond"],
marksize = [0.2, 0.3, 0.3, 0.4],
title_fontsize = "12",
label_fontsize = "8",
legend_fontsize = "9",
legend_x = "90",
legend_y = "70",
colors = ["0 0 0",
".6 .6 .6",
".2 .2 .2",
".8 .8 .8",
".4 .4 .4"]
)
mfgraph.make_eps(graph_out, "%s_%s_speedup_line" % (name, label), "xref_figures")
mfgraph.make_excel_line(name="%s-%s" % (name, label), data=data);
def make_microbench_speedup_line2(jgraphs, name, runs, bw, protocol, nest, label, minopen):
xlabel = "Processors"
ylabel = "Run Time"
#proc_values = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
# 11, 12, 13, 14, 15,
# 16, 17, 18, 19, 20,
# 21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
# 31]
proc_values = [1, 3, 7, 15, 24, 31]
read_set = None
data = []
for run in runs:
#print run
#protocol = protocol_map[run[2]]
line = [run[0]]
base_cycles = 0.0
for procs in proc_values:
#print procs
lst = []
#read_set_str = "%s" % read_set
glob_str = "%s/%s/%s-%dp-*%s-%dnx-%dminopen-%d-*.stats" % (results_dir, run[1], run[1], procs, protocol, nest, minopen, bw)
#glob_str = "%s/%s/%s*-%dp-default-%s-%dnx-%d-*.stats" % (results_dir, run[1], run[1], procs, protocol, nesting, bw)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
#exit
continue
for file in files:
print file
ruby_cycles = get_float_stat(file, "Ruby_cycles")/1000000.0
#divide by procs?
#print "ruby_cycles: %f" % ruby_cycles
lst.append(ruby_cycles)
cycles = mfgraph.mean(lst)
conf = mfgraph.confidence_interval_95_percent(lst)
#print "95 conf: %f" % conf
if procs == 1:
base_cycles = cycles
print "base_cycles is: %f" % base_cycles
line.append([procs, base_cycles/cycles, base_cycles/(cycles - conf), base_cycles/(cycles + conf)])
data.append(line)
linear = ["Linear"]
for p in proc_values:
linear.append([p, p, p, p])
data.append(linear)
#print data
jgraphs.append(mfgraph.line_graph(data,
title = name,
ylabel = "Speedup",
xlabel = "Threads",
xsize = 4.5,
ysize = 6.0,
line_thickness = 2.0,
legend_x = "90",
marktype = ["circle", "box", "triangle", "diamond"],
#marksize = [0.4, 0.4, 0.4, 0.5],
))
def make_microbench_combined_speedup_line(jgraphs, name, runs, bw, protocol, label):
xlabel = "Processors"
ylabel = "Run Time"
#proc_values = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
# 11, 12, 13, 14, 15,
# 16, 17, 18, 19, 20,
# 21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
# 31]
proc_values = [1, 3, 7, 15, 24, 31]
minopen_values = [40, 35]
nest_values = [1, 4]
read_set = None
data = []
for run in runs:
line = [run[0]]
base_cycles = 0.0
for procs in proc_values:
lst = []
glob_str = "%s/%s/%s-%dp-*%s-%snx-%sminopen-%d-*.stats" % (results_dir, run[1], run[1], procs, protocol, run[3], run[2], bw)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
continue
for file in files:
print file
ruby_cycles = get_float_stat(file, "Ruby_cycles")/1000000.0
#divide by procs?
#print "ruby_cycles: %f" % ruby_cycles
lst.append(ruby_cycles)
cycles = mfgraph.mean(lst)
conf = mfgraph.confidence_interval_95_percent(lst)
#print "95 conf: %f" % conf
if procs == 1:
base_cycles = cycles
#print "base_cycles is: %f" % base_cycles
# print "cycles is: ", base_cycles/cycles
line.append([procs, base_cycles/cycles, base_cycles/(cycles - conf), base_cycles/(cycles + conf)])
data.append(line)
#linear = ["Linear"]
#for p in proc_values:
# linear.append([p, p, p, p])
#data.append(linear)
#print data
graph_out = mfgraph.line_graph(data,
ylabel = "Speedup",
xlabel = "Threads",
label_fontsize = "10",
xsize = 2.5,
ysize = 2.3,
line_thickness = 2.0,
legend_x = "75",
legend_y = "60",
legend_fontsize = "10",
marktype = ["circle", "box", "triangle", "diamond"],
#marksize = [0.4, 0.4, 0.4, 0.5],
)
jgraphs.append(graph_out)
mfgraph.make_eps(graph_out, label, "btree")
if make_excel_files:
mfgraph.make_excel_line(name=label, data=data);
def make_microbench_bar(jgraphs, name, runs, bw, protocol_map, label):
xlabel = "Processors"
ylabel = "Run Time"
#read_set = 64
read_set = None
bars = []
proc_values = [2, 4, 8, 16, 31]
#proc_values = [1, 2, 8, 15]
#proc_values = [1, 2]
for run in runs:
#print run
protocol = protocol_map[run[2]]
bar = [run[0]]
for procs in proc_values:
#print procs
lst = []
#read_set_str = "%s" % read_set
#glob_str = "%s/%s/%s-%sk-%dp-default-%s-%d-*.stats" % (results_dir, run[1], run[1], read_set_str, procs, protocol, bw)
#glob_str = "%s/%s/%s*-%dp-default-%s-%d-*.stats" % (results_dir, run[1], run[1], procs, protocol, bw)
glob_str = "%s/%s/%s*-%dp-*%s-%d-*.stats" % (results_dir, run[1], run[1], procs, protocol, bw)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
#exit
continue
for file in files:
#print file
ruby_cycles = get_float_stat(file, "Ruby_cycles")/1000000.0
#print "ruby_cycles: %d" % ruby_cycles
lst.append(ruby_cycles)
cycles = mfgraph.mean(lst)
print lst
conf = mfgraph.confidence_interval_95_percent(lst)
bar.append(["%d" % procs, [cycles, cycles - conf, cycles + conf]])
bars.append(bar)
#print bars
jgraphs.append(mfgraph.stacked_bar_graph(bars,
bar_segment_labels = ["runtime"],
xsize = 5.0,
))
graph_out = mfgraph.stacked_bar_graph(bars,
title = "",
bar_segment_labels = ["Execution Time"],
ylabel = "Execution Time (in millions of cycles)",
#ymax = 1.50,
ymin = 0,
xsize = 2.5,
ysize = 1.778,
title_fontsize = "12",
label_fontsize = "8",
bar_name_font_size = "9",
legend_fontsize = "9",
stack_name_font_size = "9",
stack_name_location = 9,
bar_space = 1.2,
colors = ["0 0 0",
".6 .6 .6",
".2 .2 .2",
".8 .8 .8",
".4 .4 .4"]
)
mfgraph.make_eps(graph_out, "%s_%s_bar" % (name, label), "xref_figures")
if make_excel_files:
mfgraph.make_excel_bar(name=name,
data=bars)
def make_read_set(jgraphs, name, runs, bw):
protocol = "MOESI_xact_hammer_bf"
xlabel = "Processors"
ylabel = "Run Time"
bars = []
read_set_sizes = [4, 8, 16, 32, 64]
procs = 7
for run in runs:
bar = [run[0]]
for read_set in read_set_sizes:
lst = []
files = glob.glob("%s/%s/%s-%dk-%dp-*%s-%d-*.stats" % (results_dir, run[1], run[1], read_set, procs, protocol, bw))
for file in files:
#print file
lst.append(get_float_stat(file, "Ruby_cycles"))
#print lst
cycles = mfgraph.mean(lst)
conf = mfgraph.confidence_interval_95_percent(lst)
#print conf
bar.append(["%dk" % read_set, cycles, cycles - conf, cycles + conf])
bars.append(bar)
#print bars
jgraphs.append(mfgraph.stacked_bar_graph(bars,
bar_segment_labels = ["runtime"],
xsize = 5.0,
))
graph_out = mfgraph.stacked_bar_graph(bars,
title = "",
bar_segment_labels = ["Execution Time"],
ylabel = "Execution Time (in millions of cycles)",
#ymax = 1.50,
ymin = 0,
xsize = 3.5,
ysize = 1.778,
title_fontsize = "12",
label_fontsize = "8",
bar_name_font_size = "8",
legend_fontsize = "9",
stack_name_font_size = "9",
stack_name_location = 9,
bar_space = 1.2,
colors = ["1 1 1",
".8 .8 .8",
".6 .6 .6",
".4 .4 .4",
"0 0 0"]
)
mfgraph.make_eps(graph_out, "%s_read_set" % name, "xref_figures")
if make_excel_files:
mfgraph.make_excel_bar(name="%s_read_set" % name, data=bars)
def make_norm_runtime(jgraphs, pairs, protocol, label):
xlabel = "Processors"
ylabel = "Speedup"
bars = []
proc_values = [1, 2, 4, 8, 16, 32]
for pair in pairs:
bar = [pair[0]]
for procs in proc_values:
#bar = []
lst = []
#glob_str = "%s/%s/%s-%dp-default-%s*.stats" % (results_dir, pair[1], pair[1], procs, protocol)
glob_str = "%s/%s/%s-%dp*-*%s-*.stats" % (results_dir, pair[1], pair[1], procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "%s not found" % glob_str
continue
for file in files:
lst.append(get_int_stat(file, "Ruby_cycles"))
cycles_base = mfgraph.mean(lst)
lst = []
#files = glob.glob("%s/%s/%s-%dp-default-%s*.stats" % (results_dir, pair[2], pair[2], procs, protocol))
#protocol = "MESI_SMP_LogTM_directory"
glob_str = "%s/%s/%s-%dp*-*%s-*.stats" % (results_dir, pair[2], pair[2], procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "%s not found" % glob_str
continue
for file in files:
print get_int_stat(file, "Ruby_cycles")
lst.append(get_int_stat(file, "Ruby_cycles"))
cycles_test = mfgraph.mean(lst)
print "cycles_test: %d, cycles_base %d", (cycles_test, cycles_base)
norm_exe = float(cycles_base)/float(cycles_test)
bar.append(["%d" % procs, norm_exe])
#bar += ["%d" % procs, ["TM", cycles_test], ["L", cycles_base]]
bars.append(bar)
jgraphs.append(mfgraph.stacked_bar_graph(bars,
bar_segment_labels = ["runtime"],
#xsize = 5.0,
#ymax = 5.0,
))
graph_out = mfgraph.stacked_bar_graph(bars,
title = "",
bar_segment_labels = ["Execution Time"],
ylabel = "Speedup ",
ymax = 5.0,
ymin = 0,
xsize = 2.5,
ysize = 1.778,
title_fontsize = "12",
label_fontsize = "8",
bar_name_font_size = "5",
legend_fontsize = "9",
stack_name_font_size = "5",
stack_name_location = 9,
bar_space = 1.2,
colors = ["1 0 1",
".8 .8 .8",
".6 .6 .6",
".4 .4 .4",
"0 0 0"])
mfgraph.make_eps(graph_out, "%s_norm" % label, "xref_figures")
if make_excel_files:
print bars
mfgraph.make_excel_bar("speedup_%s" % label, bars)
def make_abs_runtime(jgraphs, pairs, procs, protocol, label):
xlabel = "Processors"
ylabel = "Run Time"
bars = []
for pair in pairs:
#print pair[0]
bar = []
lst = []
l_protocol = "MESI_SMP_LogTM_directory"
glob_str = "%s/%s/%s-%dp-*%s-*.stats" % (results_dir, pair[1], pair[1], procs, l_protocol)
files = glob.glob(glob_str)
if files == []:
print "%s not found" % glob_str
return
for file in files:
lst.append(get_int_stat(file, "Ruby_cycles")/1000000.0)
cycles_base = mfgraph.mean(lst)
base_conf = mfgraph.confidence_interval_95_percent(lst)
lst = []
#protocol="MESI_SMP_LogTM_directory"
glob_str = "%s/%s/%s-%dp-*%s-*.stats" % (results_dir, pair[2], pair[2], procs, protocol)
#glob_str = "%s/%s/%s-%dp*-default-%s*.stats" % (results_dir, pair[2], pair[2], procs, pair[3])
files = glob.glob(glob_str)
if files == []:
print "%s not found" % glob_str
return
for file in files:
lst.append(get_int_stat(file, "Ruby_cycles")/1000000.0)
cycles_test = mfgraph.mean(lst)
test_conf = mfgraph.confidence_interval_95_percent(lst)
norm_exe = float(cycles_test)/float(cycles_base)
#bar.append(["%d" % procs, norm_exe])
bar += [pair[0],
["LogTM", [cycles_test, cycles_test - test_conf, cycles_test + test_conf]],
["Locks", [cycles_base, cycles_base - base_conf, cycles_base + base_conf]]
]
bars.append(bar)
jgraphs.append(mfgraph.stacked_bar_graph(bars,
bar_segment_labels = ["runtime"],
xsize = 5.0,
))
graph_out = mfgraph.stacked_bar_graph(bars,
title = "",
bar_segment_labels = ["Execution Time"],
ylabel = "Execution Time (in millions of cycles)",
#ymax = 1.50,
ymin = 0,
xsize = 2.5,
ysize = 1.778,
title_fontsize = "12",
label_fontsize = "8",
bar_name_font_size = "9",
legend_fontsize = "9",
stack_name_font_size = "9",
stack_name_location = 9,
bar_space = 1.2,
colors = ["1 1 1",
".8 .8 .8",
".6 .6 .6",
".4 .4 .4",
"0 0 0"])
mfgraph.make_eps(graph_out, "%s_abs" % label, "xref_figures")
if make_excel_files:
mfgraph.make_excel_bar(name="splash_abs",
data=bars)
def make_distribution(jgraphs, benchmarks, procs, dist, stat):
protocol = "MESI_SMP_LogTM_directory"
lines = []
max_index = 0
for (name, benchmark) in benchmarks:
#glob_str = "%s/%s/%s-%dp-default-%s*.stats" % (results_dir, benchmark, benchmark, procs, protocol)
glob_str = "%s/%s/%s-%dp*-*%s*.stats" % (results_dir, benchmark, benchmark, procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
exit
data = []
for file in files:
grep_lines = mfgraph.grep(file, stat[0])
tokens = string.split(grep_lines[0])
lst = []
pipe_count = 0
count = 0
count_next = 0
bin_size_next = 0
bin_size = 0
index = 0
for token in tokens:
#print token
if token == '|':
pipe_count += 1
elif token == 'count:':
count_next = 1
elif token == '[binsize:':
bin_size_next = 1
elif bin_size_next == 1:
bin_size_next = 0
bin_size = int(token)
#print "BIN_SIZE = %d" % bin_size
elif count_next == 1:
count_next = 0
count = int(token)
elif token == ']':
pipe_count = 0
elif pipe_count >= 2:
lst.append([index*bin_size, float(token)])
index += 1
if index > max_index:
max_index = index
if dist == "CDF":
data += mfgraph.cdf(count, lst)
elif dist == "PDF":
#lst.append([index, 0])
data += mfgraph.pdf(count, lst)
elif dist == "WPDF":
data += mfgraph.w_pdf(count, lst)
else:
print "ERROR, distribution %s not supported." % dist
exit(0)
lines.append(mfgraph.merge_data(name, data))
if dist == "CDF":
for line in lines[1:]:
line.append([max_index, 1.0, 1.0, 1.0])
graph_out = mfgraph.line_graph(lines,
title = "",
xlabel = stat[1],
ylabel = dist,
xsize = 4.5
)
jgraphs.append(graph_out)
graph_out = mfgraph.line_graph(lines,
title = "",
xlabel = stat[1],
ylabel = dist,
ymax = 1.0,
title_fontsize = "12",
label_fontsize = "8",
bar_name_font_size = "9",
legend_fontsize = "9",
legend_x = "50",
line_thickness = 1.5,
#xlog = 2,
xsize = 2.5,
ysize = 1.778)
mfgraph.make_eps(graph_out, "%s-%s" % (stat[2], dist), "xref_figures")
if make_excel_files:
mfgraph.make_excel_line(name="%s-%s" % (stat[2], dist),
data=lines)
def make_dist_table(benchmarks, procs, stat):
protocol = "MESI_SMP_LogTM_directory"
print
print "DISTRIBUTION TABLE--%s" % stat[1]
bins = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024]
block_size = 64
max_index = 0
for (name, benchmark) in benchmarks:
data = {}
for bin in bins:
data[bin] = 0;
#glob_str = "%s/%s/%s-%dp-default-%s*.stats" % (results_dir, benchmark, benchmark, procs, protocol)
glob_str = "%s/%s/%s-%dp*-*%s*.stats" % (results_dir, benchmark, benchmark, procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
exit
for file in files:
grep_lines = mfgraph.grep(file, stat[0])
tokens = string.split(grep_lines[0])
lst = []
pipe_count = 0
count = 0
count_next = 0
bin_size_next = 0
bin_size = 0
index = 0
for token in tokens:
#print token
if token == '|':
pipe_count += 1
elif token == 'count:':
count_next = 1
elif token == '[binsize:':
bin_size_next = 1
elif bin_size_next == 1:
bin_size_next = 0
bin_size = int(token)
#print "BIN_SIZE = %d" % bin_size
elif count_next == 1:
count_next = 0
count = int(token)
elif token == ']':
pipe_count = 0
elif pipe_count >= 2:
lst.append([index*bin_size, int(token)])
index += 1
if index > max_index:
max_index = index
for tuple in lst:
last_bin = 0
for bin in bins:
if tuple[0] >= last_bin and tuple[0] < bin:
#print "adding %f" % tuple[1]
data[bin] = data[bin] + tuple[1]
last_bin = bin
print "%s for %s: " % (stat[1], name)
for bin in bins:
print "%d B\t%d" % ((bin*block_size), data[bin])
def make_stall_histogram(jgraphs, benchmarks, protocol):
stat = "xact_stall_occupancy"
bins = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]
processors = [4, 8, 12, 16, 32]
bars = []
for (name, benchmark) in benchmarks:
set = [name]
for procs in processors:
#print name
data = {}
for bin in bins:
data[bin] = 0
total_cycles = 0
trans_cycles = 0
ruby_cycles = 0
file_count = 0
#glob_str = "%s/%s/%s-%dp-default-%s*.stats" % (results_dir, benchmark, benchmark, procs, protocol)
glob_str = "%s/%s/%s-%dp*-*%s*.stall" % (results_dir, benchmark, benchmark, procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
continue
for file in files:
trans_cycles += get_int_stat(file, "Trans_cycles")
file_count += 1
grep_lines = mfgraph.grep(file, stat)
#print grep_lines
bin = 0
#print grep_lines
for line in grep_lines:
#print line
tokens = string.split(line, ":")
#print tokens
cycles = string.atoi(tokens[1])
total_cycles += cycles
#print bin
data[bin] += cycles
bin += 1
print name
#print data
#print "total_cycles = %d, ruby_cycles = %d" % (total_cycles, ruby_cycles)
print "trans_cycles = %d" % (trans_cycles)
temp = []
bar = [procs]
if file_count > 0 :
total = 0.0
if (total_cycles == 0):
total_cycles = 1
for bin in bins:
#print "%d: %f" % (bin, float(data[bin])/float(total_cycles))
point = float(data[bin])/float(trans_cycles)
#point = float(data[bin])
total += point
temp.append(total)
temp.reverse()
bar += temp
#print bar.reverse()
set.append(bar)
bars.append(set)
print bars
jgraphs.append(mfgraph.stacked_bar_graph(bars,
title = "Stall Distribution graph",
ylabel = "Normalized Stall times",
bar_segment_labels = ["runtime"],
xsize = 6.5,
#bar_name_rotate = 90.0,
legend = "on",
stack_name_location = 12,
colors = ["1 0 0", "0 0 0", "0 .5 0", "1 0 1", "1 1 0", "0.5 0 0"]
))
def make_xact_histogram(jgraphs, benchmarks, protocol):
stat = "xact_occupancy"
bins = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]
processors = [4, 8, 12, 16, 32]
bars = []
for (name, benchmark) in benchmarks:
set = [name]
for procs in processors:
#print name
data = {}
for bin in bins:
data[bin] = 0
total_cycles = 0
trans_cycles = 0
ruby_cycles = 0
file_count = 0
#glob_str = "%s/%s/%s-%dp-default-%s*.stats" % (results_dir, benchmark, benchmark, procs, protocol)
glob_str = "%s/%s/%s-%dp*-*%s*.stall" % (results_dir, benchmark, benchmark, procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
continue
for file in files:
trans_cycles += get_int_stat(file, "Total_cycles")
file_count += 1
grep_lines = mfgraph.grep(file, stat)
#print grep_lines
bin = 0
#print grep_lines
for line in grep_lines:
if (bin == 0):
data[bin] = 0
bin += 1
continue
#print line
tokens = string.split(line, ":")
#print tokens
cycles = string.atoi(tokens[1])
total_cycles += cycles
#print bin
data[bin] += cycles
bin += 1
print name
#print data
#print "total_cycles = %d, ruby_cycles = %d" % (total_cycles, ruby_cycles)
print "total_cycles = %d" % (trans_cycles)
temp = []
bar = [procs]
if file_count > 0 :
total = 0.0
if (total_cycles == 0):
total_cycles = 1
for bin in bins:
#print "%d: %f" % (bin, float(data[bin])/float(total_cycles))
point = float(data[bin])/float(trans_cycles)
#point = float(data[bin])
total += point
temp.append(total)
temp.reverse()
bar += temp
#print bar.reverse()
set.append(bar)
bars.append(set)
print bars
jgraphs.append(mfgraph.stacked_bar_graph(
bars,
title = "Xact Occupancy Distribution graph",
ylabel = "Normalized Xact times",
bar_segment_labels = ["runtime"],
xsize = 6.5,
#bar_name_rotate = 90.0,
legend = "on",
stack_name_location = 12,
colors = ["1 0 0", "0 0 0", "0 .5 0", "1 0 1", "1 1 0", "0.5 0 0"]
))
def make_aborts_graph(jgraphs, benchmarks, protocol):
bars = []
bar = []
processors = [1, 2, 4, 8, 16, 32]
for (name, benchmark) in benchmarks:
set = [name]
for procs in processors:
glob_str = "%s/%s/%s-%dp-*%s*.stats" % (results_dir, benchmark, benchmark, procs, protocol)
files = glob.glob(glob_str)
lst = []
count = []
if files == []:
print "%s not found" % glob_str
continue
for file in files:
lst.append(get_int_stat(file, "xact_aborts"))
count.append(get_int_stat(file, "^Begin_XACT"))
mean_aborts = mfgraph.mean(lst)
mean_count = mfgraph.mean(count)
if files == []:
mean_aborts = 0
mean_count = 1
norm_abort = mean_aborts / mean_count
set.append([procs,norm_abort])
bars.append(set)
#test_conf = mfgraph.confidence_interval_95_percent(lst)
#norm_exe = float(cycles_test)/float(cycles_base)
#bar.append(["%d" % procs, norm_exe])
#bar += [pair[0],
# ["LogTM", [cycles_test, cycles_test - test_conf, cycles_test + test_conf]],
# ["Locks", [cycles_base, cycles_base - base_conf, cycles_base + base_conf]]
# ]
print bars
jgraphs.append(mfgraph.stacked_bar_graph(bars,
title = "Transactional Aborts",
ylabel = "Aborts/Transaction",
bar_segment_labels = ["runtime"],
xsize = 5.0,
))
graph_out = mfgraph.stacked_bar_graph(bars,
title = "Transactional Aborts",
bar_segment_labels = ["Execution Time"],
ylabel = "Aborts/Transaction",
#ymax = 1.50,
ymin = 0,
xsize = 2.5,
ysize = 1.778,
title_fontsize = "12",
label_fontsize = "8",
bar_name_font_size = "9",
legend_fontsize = "9",
stack_name_font_size = "9",
stack_name_location = 9,
bar_space = 1.2,
colors = ["1 0 1",
".8 .8 .8",
".6 .6 .6",
".4 .4 .4",
"0 0 0"])
def make_aborts_delta(jgraphs, pairs, protocol, label):
xlabel = "Processors"
ylabel = "Speedup"
bars = []
proc_values = [1, 2, 4, 8, 16, 32]
for pair in pairs:
bar = [pair[0]]
for procs in proc_values:
lst = []
glob_str = "%s/%s/%s-%dp*-*%s-*.stats" % (results_dir, pair[1], pair[1], procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "%s not found" % glob_str
continue
for file in files:
lst.append(get_int_stat(file, "xact_aborts"))
aborts_base = mfgraph.mean(lst)
lst = []
#files = glob.glob("%s/%s/%s-%dp-default-%s*.stats" % (results_dir, pair[2], pair[2], procs, protocol))
#protocol = "MESI_SMP_LogTM_directory"
glob_str = "%s/%s/%s-%dp*-*%s-*.stats" % (results_dir, pair[2], pair[2], procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "%s not found" % glob_str
#return
continue
for file in files:
print get_int_stat(file, "xact_aborts")
lst.append(get_int_stat(file, "xact_aborts"))
aborts_test = mfgraph.mean(lst)
print "aborts_test: %d, aborts_base %d", (aborts_test, aborts_base)
delta_aborts = aborts_test - aborts_base
bar.append(["%d" % procs, delta_aborts])
bars.append(bar)
jgraphs.append(mfgraph.stacked_bar_graph(bars,
bar_segment_labels = ["runtime"],
ymin = 0,
#xsize = 5.0,
#ymax = 5.0,
))
graph_out = mfgraph.stacked_bar_graph(bars,
title = "",
bar_segment_labels = ["Execution Time"],
ylabel = "Speedup ",
ymax = 5.0,
xsize = 2.5,
ysize = 1.778,
title_fontsize = "12",
label_fontsize = "8",
bar_name_font_size = "5",
legend_fontsize = "9",
stack_name_font_size = "5",
stack_name_location = 9,
bar_space = 1.2,
colors = ["1 0 1",
".8 .8 .8",
".6 .6 .6",
".4 .4 .4",
"0 0 0"])
mfgraph.make_eps(graph_out, "aborts_delta_%s" % label, "xref_figures")
if make_excel_files:
print bars
mfgraph.make_excel_bar("aborts_delta_%s" % label, bars)
def make_scalability_lines(jgraphs, benchmarks, protocol):
xlabel = "Processors"
ylabel = "Run Time"
proc_values = [1, 2, 4, 8, 12, 16, 32]
data = []
for (name,benchmark) in benchmarks:
for procs in proc_values:
#print procs
lst = []
#read_set_str = "%s" % read_set
glob_str = "%s/%s/%s*-%dp-*%s-%d-*.stats" % (results_dir, benchmark, benchmark, procs, protocol)
files = glob.glob(glob_str)
if files == []:
print "No files match: %s" % glob_str
#exit
continue
for file in files:
#print file
ruby_cycles = get_float_stat(file, "Ruby_cycles")/1000000.0
#divide by procs?
#print "ruby_cycles: %d" % ruby_cycles
lst.append(ruby_cycles)
cycles = mfgraph.mean(lst)
#print lst
conf = mfgraph.confidence_interval_95_percent(lst)
line.append([procs, cycles, cycles - conf, cycles + conf])
data.append(line)
#print data
jgraphs.append(mfgraph.line_graph(data,
title = name,
ylabel = "Execution Time (in millions of cycles)",
xlabel = "Threads",
xsize = 4.5,
ysize = 8.0,
line_thickness = 2.0,
legend_x = "90",
marktype = ["circle", "box", "triangle", "diamond"],
#marksize = [0.4, 0.4, 0.4, 0.5],
))
#================ End Functions =========================================================
all_benchmarks = ("raytrace-trans_1",
"raytrace-locks_1",
#"radiosity-trans_1",
#"radiosity-locks_1",
"ocean-trans_66_1",
"ocean-locks_66_1",
#"barnes-trans_512_1",
#"barnes-locks_512_1",
"water-nsquared-trans-216_1",
"water-nsquared-locks-216_1",
)
directory_protocols = {}
directory_protocols["lock"] = "MESI_SMP_LogTM_directory";
directory_protocols["trans"] = "MESI_SMP_LogTM_directory";
bcast_protocols = {}
bcast_protocols["lock"] = "MOESI_hammer";
bcast_protocols["trans"] = "MOESI_xact_hammer_bf";
raytrace_runs = [
("Base", "raytrace-TM-teapot", "trans"),
("XOrder", "raytrace-XORDER-teapot", "trans")
]
radiosity_runs = [
("Base", "radiosity-TM-None", "trans"),
("XOrder", "radiosity-XORDER-None", "trans")
]
cholesky14_runs = [
("Base", "cholesky-TM-14", "trans"),
("XOrder", "cholesky-XORDER-14", "trans")
]
cholesky15_runs = [
("Base", "cholesky-TM-15", "trans"),
("XOrder", "cholesky-XORDER-15", "trans")
]
mp3d_runs = [
("Base", "mp3d-TM-128mol-1024ops", "trans"),
("XOrder", "mp3d-XORDER-128mol-1024ops", "trans")
]
splash_perf_runs = [
("RAYTRACE", "raytrace-TM-teapot", "raytrace-XORDER-teapot"),
("RADIOSITY", "radiosity-TM-None", "radiosity-XORDER-None"),
("CHOLESKY", "cholesky-TM-14", "cholesky-XORDER-14"),
("MP3D", "mp3d-TM-128mol-1024ops", "mp3d-XORDER-128mol-1024ops")
#("BARNES", "barnes-TM-512", "barnes-XORDER-512"),
#("BTREE-20", "btree-TM-priv-alloc-20pct", "btree-XORDER-None"),
]
log_size = ("xact_log_size_dist", "Transaction Log Size (in 64-Byte lines)", "write_set")
read_set_size = ("xact_read_set_size_dist", "Transaction Read Set Size (in 64-Byte lines)", "read_set")
jgraph_input = []
# # microbenchmark performance
#make_microbench_line(jgraph_input, "raytrace", raytrace_runs, 10000, directory_protocols, "dir")
#make_microbench_speedup_line(jgraph_input, "raytrace", raytrace_runs, 10000, directory_protocols, "dir")
make_microbench_line(jgraph_input, "radiosity", radiosity_runs, 10000, directory_protocols, "dir")
make_microbench_speedup_line(jgraph_input, "radiosity", radiosity_runs, 10000, directory_protocols, "dir")
#make_microbench_line(jgraph_input, "cholesky", cholesky14_runs, 10000, directory_protocols, "dir")
#make_microbench_speedup_line(jgraph_input, "cholesky", cholesky14_runs, 10000, directory_protocols, "dir")
#make_microbench_line(jgraph_input, "mp3d", mp3d_runs, 10000, directory_protocols, "dir")
#make_microbench_speedup_line(jgraph_input, "mp3d", mp3d_runs, 10000, directory_protocols, "dir")
make_norm_runtime(jgraph_input, splash_perf_runs, "MESI_SMP_LogTM_directory", "xorder")
make_aborts_delta(jgraph_input, splash_perf_runs, "MESI_SMP_LogTM_directory", "xorder")
mfgraph.run_jgraph("newpage\n".join(jgraph_input), "xref")
#make_dist_table(splash_dist_runs, 16, read_set_size)
#make_dist_table(splash_dist_runs, 16, log_size)