def gen_mpstats(benchmarks):
print "parsing..."
jgraph_input = []
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
print " %s %s" % (benchmark, config)
filenames = glob.glob(benchmark + "/" + benchmark + "*-" + config +
"-*.xterm")
for filename in filenames:
stats = get_mpstats(filename)
stats = stats[12:]
stats.reverse()
config_label = string.split(config, "-")[0]
bar = [config_label] + mfgraph.stack_bars(stats)
bars.append(bar)
stacks.append([benchmark] + bars)
jgraph_input.append(
mfgraph.stacked_bar_graph(
stacks,
bar_segment_labels=["idle", "wait", "system", "user"],
title="utilization",
ylabel="percent",
colors=[".8 .8 .8", "0 .5 0", "0 0 1", "1 0 0"],
patterns=["stripe 45", "solid", "solid", "solid"]))
column_label = "CPU minor-faults major-faults cross-calls interrupts interrupts-as-threads context-switches involuntary-context-switches migrations mutex-spins read-write-spins system-calls usr sys wt idl"
column_name = string.split(column_label)
column_name = map(string.strip, column_name)
for column in range(1, 12):
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
filenames = glob.glob(benchmark + "/" + benchmark + "*-" +
config + "-*.xterm")
for filename in filenames:
stats = get_mpstats(filename)
config_label = string.split(config, "-")[0]
bars.append([config_label, stats[column]])
stacks.append([benchmark] + bars)
jgraph_input.append(
mfgraph.stacked_bar_graph(
stacks,
title=column_name[column],
ylabel="operations/second (for each processor)",
colors=["0 0 1"],
patterns=["solid"]))
return jgraph_input
def gen_mpstats(benchmarks):
print "parsing..."
jgraph_input = []
stacks = [];
for benchmark in benchmarks:
bars = []
for config in configs:
print " %s %s" % (benchmark, config)
filenames = glob.glob(benchmark + "/" + benchmark + "*-" + config + "-*.xterm")
for filename in filenames:
stats = get_mpstats(filename)
stats = stats[12:]
stats.reverse()
config_label = string.split(config, "-")[0]
bar = [config_label] + mfgraph.stack_bars(stats)
bars.append(bar)
stacks.append([benchmark] + bars)
jgraph_input.append(mfgraph.stacked_bar_graph(stacks,
bar_segment_labels = ["idle", "wait", "system", "user"],
title = "utilization",
ylabel = "percent",
colors = [".8 .8 .8", "0 .5 0", "0 0 1", "1 0 0"],
patterns = ["stripe 45", "solid", "solid", "solid"]))
column_label = "CPU minor-faults major-faults cross-calls interrupts interrupts-as-threads context-switches involuntary-context-switches migrations mutex-spins read-write-spins system-calls usr sys wt idl"
column_name = string.split(column_label)
column_name = map(string.strip, column_name)
for column in range(1, 12):
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
filenames = glob.glob(benchmark + "/" + benchmark + "*-" + config + "-*.xterm")
for filename in filenames:
stats = get_mpstats(filename)
config_label = string.split(config, "-")[0]
bars.append([config_label, stats[column]])
stacks.append([benchmark] + bars)
jgraph_input.append(mfgraph.stacked_bar_graph(stacks,
title = column_name[column],
ylabel = "operations/second (for each processor)",
colors = ["0 0 1"],
patterns = ["solid"]))
return jgraph_input
def gen_scale(benchmarks):
configs = ["1p", "2p", "4p", "8p", "16p"]
base_config = "1p"
parameter = "Ruby_cycles"
stacks = []
print "parsing..."
for benchmark in benchmarks:
assoc_data = {}
for config in configs:
sys.stderr.write(" %s %s\n" % (benchmark, config))
numbers = []
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
for filename in filenames:
lines = mfgraph.grep(filename, parameter)
line = lines[0]
numbers.append(float(string.split(line)[1]))
med = mfgraph.median(numbers)
assoc_data[config] = med
mfgraph.normalize(assoc_data, base_config)
bars = []
stack_data = [benchmark]
for config in configs:
bars.append([config, assoc_data[config]])
stacks.append([benchmark] + bars)
print "done."
return [
mfgraph.stacked_bar_graph(
stacks, title="Scalability", ylabel="normalized runtime", colors=["0 0 1"], patterns=["solid"]
)
]
def generate_cpi(jgraphs, results_dir):
data = []
files = glob.glob("%s/*.opal" % results_dir)
#print files
for file in files:
print file
cpi = get_cpi(file)
width = get_issue_width(file)
data.append([width, cpi])
#data.sort()
#cpi_data = mfgraph.merge_data(group_title = "CPI", data = data)
cpi_bars = make_bars(fields=["CPI"], data=data)
cpi_bars.sort()
cpi_bars.insert(0, "CPI")
graph_bars = [cpi_bars]
#draw_std_line(jgraphs,
#"CPI vs. Instruction Window Size",
#"Issue Window Size",
#"CPI",
#lines)
#print graph_bars
jgraphs.append(
mfgraph.stacked_bar_graph(
graph_bars,
title="CPI vs Window Size",
bar_segment_labels=["CPI"],
ylabel="CPI",
xsize=4.0,
ysize=1.778,
))
def gen_scale(benchmarks):
configs = ["1p", "2p", "4p", "8p", "16p"]
base_config = "1p"
parameter = "Ruby_cycles"
stacks = [];
print "parsing..."
for benchmark in benchmarks:
assoc_data = {};
for config in configs:
sys.stderr.write(" %s %s\n" % (benchmark, config))
numbers = []
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
for filename in filenames:
lines = mfgraph.grep(filename, parameter);
line = lines[0]
numbers.append(float(string.split(line)[1]))
med = mfgraph.median(numbers)
assoc_data[config] = med;
mfgraph.normalize(assoc_data, base_config)
bars = []
stack_data = [benchmark]
for config in configs:
bars.append([config, assoc_data[config]])
stacks.append([benchmark] + bars)
print "done."
return [mfgraph.stacked_bar_graph(stacks,
title = "Scalability",
ylabel = "normalized runtime",
colors = ["0 0 1"],
patterns = ["solid"])]
def generate_reasons_for_fetch_stall(jgraphs, results_dir):
data = []
files = glob.glob("%s/*.opal" % results_dir)
#print files
for file in files:
tuple = get_reasons_for_fetch_stall(file)
data.append(tuple)
fetch_data = make_bars(fields=[
"I-Cache Miss", "Squash", "I-TLB Miss", "Window Full", "Fetch Barrier"
],
data=data)
fetch_bars = make_stacked(fetch_data)
fetch_bars.sort()
fetch_bars.insert(0, "Window Width")
graph_bars = [fetch_bars]
jgraphs.append(
mfgraph.stacked_bar_graph(
graph_bars,
title="Reasons for Fetch Stall vs. Window Width",
bar_segment_labels=[
"I-Cache Miss", "Squash", "I-TLB Miss", "Window Full",
"Fetch Barrier"
],
ylabel="%",
xsize=4.0,
ysize=1.778,
))
def generate_time_breakdown(jgraphs, results_dir):
# Gather ECperf data
tuple_list = get_time_breakdown_data(results_dir)
bar_fields = ["usr", "sys", "wt", "idl", "gc_idle"]
ecperf_data = make_bars(fields=bar_fields, data=tuple_list)
ecperf_bars = make_stacked(ecperf_data)
ecperf_bars.sort()
ecperf_bars.insert(0, "ECperf")
ecperf_data.sort()
ecperf_data.insert(0, "ECperf")
graph_bars = [ecperf_bars]
#print graph_bars
jgraphs.append(
mfgraph.stacked_bar_graph(
graph_bars,
title="",
bar_segment_labels=["User", "System", "I/O", "Idle", "GC Idle"],
ylabel="Execution Time (%)",
ymax=100,
ymin=0,
xsize=4.0,
ysize=1.778,
title_fontsize="12",
label_fontsize="9",
bar_name_font_size="9",
legend_fontsize="9",
stack_name_font_size="10",
stack_name_location=9,
bar_space=1.2,
colors=["1 1 1", ".8 .8 .8", ".6 .6 .6", ".4 .4 .4", "0 0 0"]))
def generate_cpi(jgraphs, results_dir):
data = []
files = glob.glob("%s/*.opal" % results_dir)
#print files
for file in files:
print file
cpi = get_cpi(file)
width = get_issue_width(file)
data.append([width, cpi])
#data.sort()
#cpi_data = mfgraph.merge_data(group_title = "CPI", data = data)
cpi_bars = make_bars(fields=["CPI"], data=data)
cpi_bars.sort()
cpi_bars.insert(0, "CPI")
graph_bars = [cpi_bars]
#draw_std_line(jgraphs,
#"CPI vs. Instruction Window Size",
#"Issue Window Size",
#"CPI",
#lines)
#print graph_bars
jgraphs.append(mfgraph.stacked_bar_graph(graph_bars,
title = "CPI vs Window Size",
bar_segment_labels = ["CPI"],
ylabel = "CPI",
xsize = 4.0,
ysize = 1.778,
))
def touched_by():
stats = [
"touched_by_block_address:",
"touched_by_weighted_block_address:",
"touched_by_macroblock_address:",
"touched_by_weighted_macroblock_address:",
# "touched_by_pc_address:",
# "touched_by_weighted_pc_address:",
]
stats_names = {
"touched_by_block_address:" : "(a) Percent blocks touched by n processors",
"touched_by_weighted_block_address:": "(b) Percent of misses to blocks touched by n processors",
"touched_by_macroblock_address:": "(c) Percent of macroblocks touched by n processors",
"touched_by_weighted_macroblock_address:": "(d) Percent of misses to macroblocks touched by n processors",
}
jgraph_input = []
cols = 1
row_space = 2.9
col_space = 3
num = 0
for stat in stats:
bars = []
for benchmark in benchmarks:
print stat, benchmark
group = [benchmark_names[benchmark]]
filenames = glob.glob("%s/*trace-profiler*.stats" % benchmark)
for filename in filenames:
line = mfgraph.grep(filename, stat)[0]
line = string.replace(line, "]", "")
line = string.replace(line, "[", "")
data = string.split(line)[2:]
data = map(float, data)
normalize_list(data)
for index in range(len(data)):
if index+1 in [1, 4, 8, 12, 16]:
group.append(["%d" % (index+1), data[index]*100.0])
else:
group.append(["", data[index]*100.0])
bars.append(group)
jgraph_input.append(mfgraph.stacked_bar_graph(bars,
title = stats_names[stat],
xsize = 6.5,
ysize = 2,
xlabel = "",
ylabel = "",
stack_space = 3,
x_translate = (num % cols) * col_space,
y_translate = (num / cols) * -row_space,
))
num += 1
mfgraph.run_jgraph("\n".join(jgraph_input), "touched-by")
def gen_misses(benchmarks):
configs = [
"1p-MOSI_bcast_opt", "2p-MOSI_bcast_opt", "4p-MOSI_bcast_opt",
"8p-MOSI_bcast_opt", "16p-MOSI_bcast_opt"
]
parameters = [
"Request_type_IFETCH", "Request_type_LD", "Request_type_ST",
"Request_type_ATOMIC"
]
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
print " %s %s" % (benchmark, config)
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
for filename in filenames:
numbers = []
lines = mfgraph.grep(filename, "instruction_executed")
line = string.split(lines[0])
insn = long(line[1])
for parameter in parameters:
lines = mfgraph.grep(filename, parameter)
line = string.split(lines[0])
map(string.strip, line)
numbers.append(1000.0 * (float(line[1]) / insn))
numbers = mfgraph.stack_bars(numbers)
config_label = string.split(config, "-")[0]
bars.append([config_label] + numbers)
stacks.append([benchmark] + bars)
labels = []
for label in parameters:
labels.append(string.split(label, "_")[2])
return [
mfgraph.stacked_bar_graph(
stacks,
bar_segment_labels=labels,
title="Breakdown of misses",
ylabel="misses per thousand instructions",
patterns=["solid"],
)
]
def gen_sharing(benchmarks, normalize=1):
configs = ["1p", "2p", "4p", "8p", "16p"]
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
print " %s %s" % (benchmark, config)
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
for filename in filenames:
lines = mfgraph.grep(filename, "instruction_executed")
line = string.split(lines[0])
insn = long(line[1])
numbers = get_sharing(filename)
if normalize:
sum = reduce(lambda x, y: x + y, numbers)
for index in range(len(numbers)):
numbers[index] = (numbers[index] / sum) * 100.0
else:
for index in range(len(numbers)):
numbers[index] = (numbers[index] /
float(insn)) * 1000.0
numbers = mfgraph.stack_bars(numbers)
bars.append([config] + numbers)
stacks.append([benchmark] + bars)
if normalize:
y_axis_label = "percent of misses"
else:
y_axis_label = "misses per thousand instructions",
return [
mfgraph.stacked_bar_graph(
stacks,
bar_segment_labels=labels,
title="Breakdown of misses",
ylabel=y_axis_label,
patterns=[
"stripe -45", "stripe -45", "stripe -45", "solid", "solid"
],
)
]
def generate_macro_bar():
processor = 16
bandwidth = 1600
stat = "Ruby_cycles"
stacks = []
for benchmark in benchmarks[1:]:
bars = []
modules = ["MOSI_bcast_opt_4", "MOSI_GS_4", "MOSI_mcast_aggr_4"]
#norm = mfgraph.average(get_data(benchmark, processor=processor, module="MOSI_mcast_aggr_4", bandwidth=bandwidth, stat=stat))
norm = mfgraph.average(get_data(benchmark, processor=processor, module="MOSI_bcast_opt_4", bandwidth=bandwidth, stat=stat))
for module in modules:
if module == "MOSI_mcast_aggr_4":
bars.append(["", 0])
else:
data = get_data(benchmark, processor=processor, module=module, bandwidth=bandwidth, stat=stat)
value = mfgraph.average(data)
stddev = mfgraph.stddev(data)
if (stddev/value)*100.0 > 1.0: # only plot error bars if they are more than 1%
bars.append([protocol_name[module], [norm/value, norm/(value+stddev), norm/(value-stddev)]])
else:
bars.append([protocol_name[module], [norm/value, norm/(value+stddev), norm/(value-stddev)]])
# bars.append([protocol_name[module], norm/value])
stacks.append([workload_name[benchmark]] + bars)
jgraph_input = mfgraph.stacked_bar_graph(stacks,
colors = ["1 0 0", "0 .5 0", "0 0 1", "0 1 1", "1 0 1"],
# colors = [".85 .85 .85", ".5 .5 .5", ".45 .45 .45"],
patterns = ["solid", "stripe -45"],
ymax = 1.5,
xsize = 2.7,
ysize = 2.3,
label_fontsize = "9",
hash_label_fontsize = "9",
stack_name_font_size = "9",
bar_name_font_size = "9",
bar_name_rotate = 90.0,
stack_name_location = 28.0,
ylabel = "normalized performance",
yhash = 0.2,
ymhash = 1,
)
mfgraph.run_jgraph(jgraph_input, "bash-macro-talk-bars")
def gen_sharing_histo():
bars = []
for benchmark in benchmarks:
filenames = glob.glob("*/%s-gs320*.stats" % benchmark)
if len(filenames) != 1:
continue
filename = filenames[0]
gets_dist = get_histo(filename, "gets_sharing_histogram:")
getx_dist = get_histo(filename, "getx_sharing_histogram:")
total_misses = get_data(filename, "Total_misses:")
gets_dist = map(lambda x: 100.0 * (float(x) / total_misses), gets_dist)
gets_dist += [0] * 14 # fill in the end with zeros
getx_dist = map(lambda x: 100.0 * (float(x) / total_misses), getx_dist)
getx_dist = getx_dist[0:3] + [
reduce(lambda x, y: x + y, getx_dist[3:7])
] + [reduce(lambda x, y: x + y, getx_dist[7:])]
gets_dist = gets_dist[0:3] + [
reduce(lambda x, y: x + y, gets_dist[3:7])
] + [reduce(lambda x, y: x + y, gets_dist[7:])]
# getx_dist = mfgraph.stack_bars(getx_dist)
# gets_dist = mfgraph.stack_bars(gets_dist)
labels = ["0", "1", "2", "3-7", "8+"]
bars.append([benchmark_names[benchmark]] +
map(lambda l, gets, getx:
(l, gets + getx, getx), labels, gets_dist, getx_dist))
jgraph_input = mfgraph.stacked_bar_graph(
bars,
bar_segment_labels=["Get shared", "Get exclusive"],
xsize=7,
ysize=3,
ylabel="Percent of all misses",
colors=["1 0 0", "0 0 1"],
patterns=["solid", "stripe -45"],
bar_name_font_size="10",
stack_name_location=10.0,
legend_x="31",
legend_y="87",
)
mfgraph.run_jgraph(jgraph_input, "sharers")
def gen_protocol(benchmarks):
# configs = ["8p-perfect", "8p-MOSI_bcast_opt", "8p-MOSI_GS"]
configs = ["8p-MOSI_bcast_opt", "8p-MOSI_GS"]
base_config = "8p-MOSI_bcast_opt"
parameter = "Ruby_cycles"
stacks = [];
print "parsing..."
for benchmark in benchmarks:
assoc_data = {};
for config in configs:
sys.stderr.write(" %s %s\n" % (benchmark, config))
numbers = []
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
for filename in filenames:
lines = mfgraph.grep(filename, parameter);
line = lines[0]
numbers.append(float(string.split(line)[1]))
print numbers
med = mfgraph.median(numbers)
stddev = mfgraph.stddev(numbers)
min_val = min(numbers)
max_val = max(numbers)
assoc_data[config] = [med, min_val, max_val];
mfgraph.normalize(assoc_data, base_config)
bars = []
stack_data = [benchmark]
for config in configs:
bars.append([config, assoc_data[config]])
stacks.append([benchmark] + bars)
print "done."
print stacks
return [mfgraph.stacked_bar_graph(stacks,
title = "Snooping vs Directory",
ylabel = "normalized runtime",
colors = [".5 .5 1"],
patterns = ["solid"])]
def gen_cache_state(benchmarks):
configs = ["1p", "2p", "4p", "8p", "16p"]
parameters = ["GETS NP", "GETS I", "GETX NP", "GETX I", "GETX S", "GETX O"]
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
print " %s %s" % (benchmark, config), filenames
numbers = []
for parameter in parameters:
sum = 0
for filename in filenames:
# print benchmark, config, parameter, filename
lines = mfgraph.grep(filename, "instruction_executed")
line = string.split(lines[0])
insn = long(line[1])
lines = mfgraph.grep(filename, parameter)
for line in lines:
fields = string.split(line)
# print fields
sum += int(fields[3])
numbers.append(float(sum) / float(insn))
numbers = mfgraph.stack_bars(numbers)
bars.append([config] + numbers)
stacks.append([benchmark] + bars)
labels = []
for label in parameters:
labels.append(label)
return [
mfgraph.stacked_bar_graph(
stacks,
bar_segment_labels=labels,
title="Cache Misses by state",
ylabel="Number",
)
]
def generate_reasons_for_fetch_stall(jgraphs, results_dir):
data = []
files = glob.glob("%s/*.opal" % results_dir)
#print files
for file in files:
tuple = get_reasons_for_fetch_stall(file)
data.append(tuple)
fetch_data = make_bars(fields=["I-Cache Miss", "Squash", "I-TLB Miss", "Window Full", "Fetch Barrier"],
data=data)
fetch_bars = make_stacked(fetch_data)
fetch_bars.sort()
fetch_bars.insert(0, "Window Width")
graph_bars = [fetch_bars]
jgraphs.append(mfgraph.stacked_bar_graph(graph_bars,
title = "Reasons for Fetch Stall vs. Window Width",
bar_segment_labels = ["I-Cache Miss", "Squash", "I-TLB Miss", "Window Full", "Fetch Barrier"],
ylabel = "%",
xsize = 4.0,
ysize = 1.778,
))
def generate_reasons_for_retire_stall(jgraphs, results_dir):
data = []
files = glob.glob("%s/*.opal" % results_dir)
#print files
for file in files:
tuple = get_reasons_for_retire_stall(file)
data.append(tuple)
retire_data = make_bars(fields=["Updating", "Squash", "Limit"],
data=data)
retire_bars = make_stacked(retire_data)
retire_bars.sort()
retire_bars.insert(0, "JBB")
graph_bars = [retire_bars]
jgraphs.append(mfgraph.stacked_bar_graph(graph_bars,
title = "Reasons for Retire Stall vs. Window Width",
bar_segment_labels = ["Updating", "Squash", "Limit"],
ylabel = "%",
xsize = 4.0,
ysize = 1.778,
))
def generate_bar_example(jgraphs):
bars = [
[
"group1",
["bar1", 20, 10, 5],
["bar2", 10, 5, 2.5],
],
[
"group2",
["bar1", 80, 40, 10],
["bar2", [100, 90, 110], 50, 10], # note, this has an error bar
["bar3", 30, 25, 5],
]
]
jgraphs.append(
mfgraph.stacked_bar_graph(
bars,
bar_segment_labels=["segment1", "segment2", "segment3"],
xsize=5.0,
))
def generate_reasons_for_retire_stall(jgraphs, results_dir):
data = []
files = glob.glob("%s/*.opal" % results_dir)
#print files
for file in files:
tuple = get_reasons_for_retire_stall(file)
data.append(tuple)
retire_data = make_bars(fields=["Updating", "Squash", "Limit"], data=data)
retire_bars = make_stacked(retire_data)
retire_bars.sort()
retire_bars.insert(0, "JBB")
graph_bars = [retire_bars]
jgraphs.append(
mfgraph.stacked_bar_graph(
graph_bars,
title="Reasons for Retire Stall vs. Window Width",
bar_segment_labels=["Updating", "Squash", "Limit"],
ylabel="%",
xsize=4.0,
ysize=1.778,
))
def gen_cache_state(benchmarks):
configs = ["1p", "2p", "4p", "8p", "16p"]
parameters = ["GETS NP", "GETS I", "GETX NP", "GETX I", "GETX S", "GETX O"]
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
print " %s %s" % (benchmark, config), filenames
numbers = []
for parameter in parameters:
sum = 0
for filename in filenames:
# print benchmark, config, parameter, filename
lines = mfgraph.grep(filename, "instruction_executed");
line = string.split(lines[0])
insn = long(line[1])
lines = mfgraph.grep(filename, parameter);
for line in lines:
fields = string.split(line)
# print fields
sum += int(fields[3])
numbers.append(float(sum)/float(insn))
numbers = mfgraph.stack_bars(numbers)
bars.append([config] + numbers)
stacks.append([benchmark] + bars)
labels = []
for label in parameters:
labels.append(label)
return [mfgraph.stacked_bar_graph(stacks,
bar_segment_labels = labels,
title = "Cache Misses by state",
ylabel = "Number",
)]
def gen_data_size(benchmarks):
configs = ["1p-MOSI_bcast_opt", "2p-MOSI_bcast_opt", "4p-MOSI_bcast_opt", "8p-MOSI_bcast_opt", "16p-MOSI_bcast_opt"]
parameters = ["C GET_INSTR", "C GETS", "C GETX"]
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
print " %s %s" % (benchmark, config)
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
for filename in filenames:
numbers = []
for parameter in parameters:
lines = mfgraph.grep(filename, parameter);
line = string.split(lines[0])
map(string.strip, line)
num = string.split(line[2], "%")
num = (64L*(long(num[0])))/(1024.0*1024.0)
numbers.append(num)
numbers = mfgraph.stack_bars(numbers)
number = reduce(lambda x,y:x+y, numbers)
config_label = string.split(config, "-")[0]
bars.append([config_label] + [number])
stacks.append([benchmark] + bars)
# labels = []
# for label in parameters:
# labels.append(string.split(label)[1])
return [mfgraph.stacked_bar_graph(stacks,
# bar_segment_labels = labels,
title = "Memory touched",
ylabel = "Mbytes",
patterns = ["solid"],
xsize = 8.5,
)]
def gen_sharing(benchmarks, normalize = 1):
configs = ["1p", "2p", "4p", "8p", "16p"]
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
print " %s %s" % (benchmark, config)
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
for filename in filenames:
lines = mfgraph.grep(filename, "instruction_executed");
line = string.split(lines[0])
insn = long(line[1])
numbers = get_sharing(filename)
if normalize:
sum = reduce(lambda x,y: x+y, numbers)
for index in range(len(numbers)):
numbers[index] = (numbers[index] / sum) * 100.0
else:
for index in range(len(numbers)):
numbers[index] = (numbers[index] / float(insn)) * 1000.0
numbers = mfgraph.stack_bars(numbers)
bars.append([config] + numbers)
stacks.append([benchmark] + bars)
if normalize:
y_axis_label = "percent of misses"
else:
y_axis_label = "misses per thousand instructions",
return [mfgraph.stacked_bar_graph(stacks,
bar_segment_labels = labels,
title = "Breakdown of misses",
ylabel = y_axis_label,
patterns = ["stripe -45", "stripe -45", "stripe -45", "solid", "solid"],
)]
def generate_time_breakdown(jgraphs, results_dir):
# Gather ECperf data
tuple_list = get_time_breakdown_data(results_dir)
bar_fields = ["usr", "sys", "wt", "idl", "gc_idle"]
ecperf_data = make_bars(fields=bar_fields, data=tuple_list)
ecperf_bars = make_stacked(ecperf_data)
ecperf_bars.sort()
ecperf_bars.insert(0, "ECperf")
ecperf_data.sort()
ecperf_data.insert(0, "ECperf")
graph_bars = [ecperf_bars]
#print graph_bars
jgraphs.append(mfgraph.stacked_bar_graph(graph_bars,
title = "",
bar_segment_labels = ["User", "System", "I/O", "Idle", "GC Idle"],
ylabel = "Execution Time (%)",
ymax = 100,
ymin = 0,
xsize = 4.0,
ysize = 1.778,
title_fontsize = "12",
label_fontsize = "9",
bar_name_font_size = "9",
legend_fontsize = "9",
stack_name_font_size = "10",
stack_name_location = 9,
bar_space = 1.2,
colors = ["1 1 1",
".8 .8 .8",
".6 .6 .6",
".4 .4 .4",
"0 0 0"]
))
def gen_sharing_histo():
bars = []
for benchmark in benchmarks:
filenames = glob.glob("*/%s-gs320*.stats" % benchmark)
if len(filenames) != 1:
continue
filename = filenames[0]
gets_dist = get_histo(filename, "gets_sharing_histogram:")
getx_dist = get_histo(filename, "getx_sharing_histogram:")
total_misses = get_data(filename, "Total_misses:")
gets_dist = map(lambda x : 100.0 * (float(x) / total_misses), gets_dist)
gets_dist += [0] * 14 # fill in the end with zeros
getx_dist = map(lambda x : 100.0 * (float(x) / total_misses), getx_dist)
getx_dist = getx_dist[0:3] + [reduce(lambda x,y:x+y, getx_dist[3:7])] + [reduce(lambda x,y:x+y, getx_dist[7:])]
gets_dist = gets_dist[0:3] + [reduce(lambda x,y:x+y, gets_dist[3:7])] + [reduce(lambda x,y:x+y, gets_dist[7:])]
# getx_dist = mfgraph.stack_bars(getx_dist)
# gets_dist = mfgraph.stack_bars(gets_dist)
labels = ["0", "1", "2", "3-7", "8+"]
bars.append([benchmark_names[benchmark]] + map(lambda l, gets, getx : (l, gets+getx, getx), labels, gets_dist, getx_dist))
jgraph_input = mfgraph.stacked_bar_graph(bars,
bar_segment_labels = ["Get shared", "Get exclusive"],
xsize = 7,
ysize = 3,
ylabel = "Percent of all misses",
colors = ["1 0 0", "0 0 1"],
patterns = ["solid", "stripe -45"],
bar_name_font_size = "10",
stack_name_location = 10.0,
legend_x = "31",
legend_y = "87",
)
mfgraph.run_jgraph(jgraph_input, "sharers")
def gen_misses(benchmarks):
configs = ["1p-MOSI_bcast_opt", "2p-MOSI_bcast_opt", "4p-MOSI_bcast_opt", "8p-MOSI_bcast_opt", "16p-MOSI_bcast_opt"]
parameters = ["Request_type_IFETCH", "Request_type_LD", "Request_type_ST", "Request_type_ATOMIC"]
stacks = []
for benchmark in benchmarks:
bars = []
for config in configs:
print " %s %s" % (benchmark, config)
filenames = glob.glob(benchmark + "/*-" + config + "-*.stats")
for filename in filenames:
numbers = []
lines = mfgraph.grep(filename, "instruction_executed");
line = string.split(lines[0])
insn = long(line[1])
for parameter in parameters:
lines = mfgraph.grep(filename, parameter);
line = string.split(lines[0])
map(string.strip, line)
numbers.append(1000.0*(float(line[1])/insn))
numbers = mfgraph.stack_bars(numbers)
config_label = string.split(config, "-")[0]
bars.append([config_label] + numbers)
stacks.append([benchmark] + bars)
labels = []
for label in parameters:
labels.append(string.split(label, "_")[2])
return [mfgraph.stacked_bar_graph(stacks,
bar_segment_labels = labels,
title = "Breakdown of misses",
ylabel = "misses per thousand instructions",
patterns = ["solid"],
)]
def touched_by():
stats = [
"touched_by_block_address:",
"touched_by_weighted_block_address:",
"touched_by_macroblock_address:",
"touched_by_weighted_macroblock_address:",
# "touched_by_pc_address:",
# "touched_by_weighted_pc_address:",
]
stats_names = {
"touched_by_block_address:":
"(a) Percent blocks touched by n processors",
"touched_by_weighted_block_address:":
"(b) Percent of misses to blocks touched by n processors",
"touched_by_macroblock_address:":
"(c) Percent of macroblocks touched by n processors",
"touched_by_weighted_macroblock_address:":
"(d) Percent of misses to macroblocks touched by n processors",
}
jgraph_input = []
cols = 1
row_space = 2.9
col_space = 3
num = 0
for stat in stats:
bars = []
for benchmark in benchmarks:
print stat, benchmark
group = [benchmark_names[benchmark]]
filenames = glob.glob("%s/*trace-profiler*.stats" % benchmark)
for filename in filenames:
line = mfgraph.grep(filename, stat)[0]
line = string.replace(line, "]", "")
line = string.replace(line, "[", "")
data = string.split(line)[2:]
data = map(float, data)
normalize_list(data)
for index in range(len(data)):
if index + 1 in [1, 4, 8, 12, 16]:
group.append(["%d" % (index + 1), data[index] * 100.0])
else:
group.append(["", data[index] * 100.0])
bars.append(group)
jgraph_input.append(
mfgraph.stacked_bar_graph(
bars,
title=stats_names[stat],
xsize=6.5,
ysize=2,
xlabel="",
ylabel="",
stack_space=3,
x_translate=(num % cols) * col_space,
y_translate=(num / cols) * -row_space,
))
num += 1
mfgraph.run_jgraph("\n".join(jgraph_input), "touched-by")
def instant_sharers():
jgraph_input = []
gets_map = {
"N N": 1,
"Y N": 0,
}
getx_map = {
"N N N N": 1,
"N N N Y": 1,
"N N Y N": 1,
"N N Y Y": 1,
# "N Y N N" : "X",
# "N Y N Y" : "X",
# "N Y Y N" : "X",
"N Y Y Y": 0,
"Y N N N": 0,
"Y N N Y": 0,
"Y N Y N": 0,
"Y N Y Y": 0,
# "Y Y N N" : "X",
# "Y Y N Y" : "X",
# "Y Y Y N" : "X",
# "Y Y Y Y" : "X",
}
cols = 2
row_space = 2.9
col_space = 3
num = 0
bars = []
for benchmark in benchmarks:
getx_dist = [0] * 16
gets_dist = [0] * 16
print benchmark
group = [benchmark_names[benchmark]]
filename = glob.glob("%s/*trace-profiler*.stats" % benchmark)[0]
gets_mode = 0
sum = 0
for line in open(filename).readlines():
line = string.strip(line)
line = string.translate(line, string.maketrans("][", " "))
# set mode
str = "Total requests: "
if line[0:len(str)] == str:
total_requests = int(string.split(line)[2])
if line == "GETS message classifications:":
gets_mode = 1
if line == "":
gets_mode = 0
if gets_mode == 1:
#gets
key = line[0:3]
if gets_map.has_key(key):
parts = string.split(line)
sum += int(parts[2])
# no histogram
data = parts[2:3]
# shift if one
if gets_map[key] == 1:
data = [0] + data
data = map(int, data)
add_list(gets_dist, data)
else:
#getx
key = line[0:7]
if getx_map.has_key(key):
parts = string.split(line)
sum += int(parts[4])
if len(parts) > 10:
# histogram
data = parts[19:]
else:
# no histogram
data = parts[4:5]
# shift if one
if getx_map[key] == 1:
data = [0] + data
data = map(int, data)
add_list(getx_dist, data)
for i in range(len(getx_dist)):
gets_dist[i] = 100.0 * ((gets_dist[i] + getx_dist[i]) / float(sum))
getx_dist[i] = 100.0 * (getx_dist[i] / float(sum))
getx_dist = getx_dist[0:3] + [
reduce(lambda x, y: x + y, getx_dist[3:7])
] + [reduce(lambda x, y: x + y, getx_dist[7:])]
gets_dist = gets_dist[0:3] + [
reduce(lambda x, y: x + y, gets_dist[3:7])
] + [reduce(lambda x, y: x + y, gets_dist[7:])]
print getx_dist
print gets_dist
print "indirections:", 100.0 - gets_dist[0]
labels = ["0", "1", "2", "3-7", ">8"]
## labels = []
## for i in range(16):
## if i in [0, 3, 7, 11, 15]:
## labels.append("%d" % i)
## else:
## labels.append("")
bars.append([benchmark_names[benchmark]] +
map(None, labels, gets_dist, getx_dist))
print bars
jgraph_input.append(
mfgraph.stacked_bar_graph(
bars,
bar_segment_labels=["Get shared", "Get exclusive"],
xsize=7,
ysize=3,
ylabel="Percent of all misses",
legend_x="25",
legend_y="90",
))
mfgraph.run_jgraph("\n".join(jgraph_input), "instant-sharers")
def touched_by():
stats = [
"touched_by_block_address:",
"touched_by_weighted_block_address:",
# "touched_by_macroblock_address:",
# "touched_by_weighted_macroblock_address:",
# "touched_by_supermacroblock_address:",
# "touched_by_weighted_supermacroblock_address:",
# "last_n_block_touched_by",
# "last_n_macroblock_touched_by",
]
yaxis_names = [
"Percent of all blocks",
"Percent of all misses",
"Percent of all macroblocks",
"Percent of all misses",
"Percent of all macroblocks",
"Percent of all misses",
# "Percent",
# "Percent",
]
stats_names = {
"touched_by_block_address:" : "(a) Percent of data blocks (64B) touched by n processors",
"touched_by_weighted_block_address:": "(b) Percent of misses to data blocks (64B) touched by n processors",
# "touched_by_macroblock_address:": "(c) Percent of data macroblocks (1024B) touched by n processors",
# "touched_by_weighted_macroblock_address:": "(d) Percent of misses to data macroblocks (1024B) touched by n processors",
# "touched_by_supermacroblock_address:": "(e) Percent of 4kB macroblocks touched by n processors",
# "touched_by_weighted_supermacroblock_address:": "(f) Percent of misses to 4kB macroblocks touched by n processors",
# "last_n_block_touched_by" : "(e) Percent of misses touched by n processors in the last 64 misses to the block",
# "last_n_macroblock_touched_by" : "(f) Percent of misses touched by n processors in the last 64 misses to the macroblock",
}
jgraph_input = []
cols = 1
row_space = 2.2
col_space = 3
num = 0
for stat in stats:
bars = []
for benchmark in benchmarks:
print stat, benchmark
group = [benchmark_names[benchmark]]
filenames = glob.glob("*/%s-*gs320*.stats" % benchmark)
print benchmark, filenames
for filename in filenames:
line = mfgraph.grep(filename, stat)[0]
line = string.replace(line, "]", "")
line = string.replace(line, "[", "")
data = string.split(line)[2:]
# data = string.split(line)[14:]
data = map(float, data)
print data
# new_data = []
# sum = 0.0
# for item in data:
# new_data.append(item + sum)
# sum += item
# data = new_data
print data
# for index in range(len(data)):
# data[index] = data[index]/sum
print data
normalize_list(data)
for index in range(len(data)):
if index+1 in [1, 4, 8, 12, 16]:
group.append(["%d" % (index+1), data[index]*100.0])
else:
group.append(["", data[index]*100.0])
bars.append(group)
jgraph_input.append(mfgraph.stacked_bar_graph(bars,
title = stats_names[stat],
title_fontsize = "12",
title_font = "Times-Roman",
title_y = -25.0,
xsize = 6.5,
ysize = 1.5,
xlabel = "",
ymax = 100.01,
ylabel = yaxis_names[num],
colors = [".5 .5 .5"],
patterns = ["solid"],
stack_name_location = 12.0,
stack_space = 3,
x_translate = (num % cols) * col_space,
y_translate = (num / cols) * -row_space,
))
num += 1
mfgraph.run_jgraph("\n".join(jgraph_input), "touched-by")
def touched_by():
stats = [
"touched_by_block_address:",
"touched_by_weighted_block_address:",
# "touched_by_macroblock_address:",
# "touched_by_weighted_macroblock_address:",
# "touched_by_supermacroblock_address:",
# "touched_by_weighted_supermacroblock_address:",
# "last_n_block_touched_by",
# "last_n_macroblock_touched_by",
]
yaxis_names = [
"Percent of all blocks",
"Percent of all misses",
"Percent of all macroblocks",
"Percent of all misses",
"Percent of all macroblocks",
"Percent of all misses",
# "Percent",
# "Percent",
]
stats_names = {
"touched_by_block_address:":
"(a) Percent of data blocks (64B) touched by n processors",
"touched_by_weighted_block_address:":
"(b) Percent of misses to data blocks (64B) touched by n processors",
# "touched_by_macroblock_address:": "(c) Percent of data macroblocks (1024B) touched by n processors",
# "touched_by_weighted_macroblock_address:": "(d) Percent of misses to data macroblocks (1024B) touched by n processors",
# "touched_by_supermacroblock_address:": "(e) Percent of 4kB macroblocks touched by n processors",
# "touched_by_weighted_supermacroblock_address:": "(f) Percent of misses to 4kB macroblocks touched by n processors",
# "last_n_block_touched_by" : "(e) Percent of misses touched by n processors in the last 64 misses to the block",
# "last_n_macroblock_touched_by" : "(f) Percent of misses touched by n processors in the last 64 misses to the macroblock",
}
jgraph_input = []
cols = 1
row_space = 2.2
col_space = 3
num = 0
for stat in stats:
bars = []
for benchmark in benchmarks:
print stat, benchmark
group = [benchmark_names[benchmark]]
filenames = glob.glob("*/%s-*gs320*.stats" % benchmark)
print benchmark, filenames
for filename in filenames:
line = mfgraph.grep(filename, stat)[0]
line = string.replace(line, "]", "")
line = string.replace(line, "[", "")
data = string.split(line)[2:]
# data = string.split(line)[14:]
data = map(float, data)
print data
# new_data = []
# sum = 0.0
# for item in data:
# new_data.append(item + sum)
# sum += item
# data = new_data
print data
# for index in range(len(data)):
# data[index] = data[index]/sum
print data
normalize_list(data)
for index in range(len(data)):
if index + 1 in [1, 4, 8, 12, 16]:
group.append(["%d" % (index + 1), data[index] * 100.0])
else:
group.append(["", data[index] * 100.0])
bars.append(group)
jgraph_input.append(
mfgraph.stacked_bar_graph(
bars,
title=stats_names[stat],
title_fontsize="12",
title_font="Times-Roman",
title_y=-25.0,
xsize=6.5,
ysize=1.5,
xlabel="",
ymax=100.01,
ylabel=yaxis_names[num],
colors=[".5 .5 .5"],
patterns=["solid"],
stack_name_location=12.0,
stack_space=3,
x_translate=(num % cols) * col_space,
y_translate=(num / cols) * -row_space,
))
num += 1
mfgraph.run_jgraph("\n".join(jgraph_input), "touched-by")
def instant_sharers():
jgraph_input = []
gets_map = {
"N N" : 1,
"Y N" : 0,
}
getx_map = {
"N N N N" : 1,
"N N N Y" : 1,
"N N Y N" : 1,
"N N Y Y" : 1,
# "N Y N N" : "X",
# "N Y N Y" : "X",
# "N Y Y N" : "X",
"N Y Y Y" : 0,
"Y N N N" : 0,
"Y N N Y" : 0,
"Y N Y N" : 0,
"Y N Y Y" : 0,
# "Y Y N N" : "X",
# "Y Y N Y" : "X",
# "Y Y Y N" : "X",
# "Y Y Y Y" : "X",
}
cols = 2
row_space = 2.9
col_space = 3
num = 0
bars = []
for benchmark in benchmarks:
getx_dist = [0] * 16
gets_dist = [0] * 16
print benchmark
group = [benchmark_names[benchmark]]
filename = glob.glob("%s/*trace-profiler*.stats" % benchmark)[0]
gets_mode = 0
sum = 0
for line in open(filename).readlines():
line = string.strip(line)
line = string.translate(line, string.maketrans("][", " "))
# set mode
str = "Total requests: "
if line[0:len(str)] == str:
total_requests = int(string.split(line)[2])
if line == "GETS message classifications:":
gets_mode = 1;
if line == "":
gets_mode = 0;
if gets_mode == 1:
#gets
key = line[0:3]
if gets_map.has_key(key):
parts = string.split(line)
sum += int(parts[2])
# no histogram
data = parts[2:3]
# shift if one
if gets_map[key] == 1:
data = [0] + data
data = map(int, data)
add_list(gets_dist, data)
else:
#getx
key = line[0:7]
if getx_map.has_key(key):
parts = string.split(line)
sum += int(parts[4])
if len(parts) > 10:
# histogram
data = parts[19:]
else:
# no histogram
data = parts[4:5]
# shift if one
if getx_map[key] == 1:
data = [0] + data
data = map(int, data)
add_list(getx_dist, data)
for i in range(len(getx_dist)):
gets_dist[i] = 100.0 * ((gets_dist[i]+getx_dist[i]) / float(sum))
getx_dist[i] = 100.0 * (getx_dist[i] / float(sum))
getx_dist = getx_dist[0:3] + [reduce(lambda x,y:x+y, getx_dist[3:7])] + [reduce(lambda x,y:x+y, getx_dist[7:])]
gets_dist = gets_dist[0:3] + [reduce(lambda x,y:x+y, gets_dist[3:7])] + [reduce(lambda x,y:x+y, gets_dist[7:])]
print getx_dist
print gets_dist
print "indirections:", 100.0-gets_dist[0]
labels = ["0", "1", "2", "3-7", ">8"]
## labels = []
## for i in range(16):
## if i in [0, 3, 7, 11, 15]:
## labels.append("%d" % i)
## else:
## labels.append("")
bars.append([benchmark_names[benchmark]] + map(None, labels, gets_dist, getx_dist))
print bars
jgraph_input.append(mfgraph.stacked_bar_graph(bars,
bar_segment_labels = ["Get shared", "Get exclusive"],
xsize = 7,
ysize = 3,
ylabel = "Percent of all misses",
legend_x = "25",
legend_y = "90",
))
mfgraph.run_jgraph("\n".join(jgraph_input), "instant-sharers")
def generate_bar_example():
stacks=[]
bars=[]
tempval = 0.25
output_list = ""
for j in range(i):
bars=[]
numbers = []
if(float(hash_table0_results[j]) > 43200):
output_list = output_list + "graph 2 newstring fontsize 9 x " + str(tempval) + " y 107 hjc vjt rotate 90.0 : " + "inf" + "\n"
numbers.append(43200)
else:
numbers.append(hash_table0_results[j])
numbers=mfgraph.stack_bars(numbers)
bars.append([""] + numbers)
tempval += 1.1
numbers = []
if(float(hash_table1_results[j]) > 43200):
output_list = output_list + "graph 2 newstring fontsize 9 x " + str(tempval) + " y 107 hjc vjt rotate 90.0 : " + "inf" + "\n"
numbers.append(43200)
else:
numbers.append(hash_table1_results[j])
numbers=mfgraph.stack_bars(numbers)
bars.append([""] + numbers)
tempval += 1.1
numbers = []
if(float(hash_table2_results[j]) > 43200) :
output_list = output_list + "graph 2 newstring fontsize 9 x " + str(tempval) + " y 107 hjc vjt rotate 90.0 : " + "inf" + "\n"
numbers.append(43200)
else:
numbers.append(hash_table2_results[j])
numbers=mfgraph.stack_bars(numbers)
bars.append([""] + numbers)
tempval += 1.1
numbers = []
if(float(hash_table3_results[j]) > 43200):
output_list = output_list + "graph 2 newstring fontsize 9 x " + str(tempval) + " y 107 hjc vjt rotate 90.0 : " + "inf" + "\n"
numbers.append(43200)
else:
numbers.append(hash_table3_results[j])
numbers=mfgraph.stack_bars(numbers)
bars.append([""] + numbers)
stacks.append([benchmarks[j]]+ bars)
tempval += 2.15
#print stacks
return [mfgraph.stacked_bar_graph(stacks,
bar_segment_labels = labels,
title = " ",
title_y = 140,
title_fontsize = "5",
ylabel = "Total Time (sec)",
#xlabel = "Number of pointer jumps",
colors = ["0.375 0.375 0.375", "0.875 0.875 0.875", "0 0 0", "0.625 0.625 0.625"],
legend_x = "2",
legend_y = "125",
legend_type = "Manual",
legend_type_x=[0, 20, 0, 20],
legend_type_y=[10, 10, 0, 0] ,
clip = 300,
ysize = 1.1,
xsize = 6,
ymax = 43200,
patterns = ["solid"],
stack_name_rotate = 25.0,
stack_name_font_size = "6", #bmarks names
label_fontsize = "6", #y-axis name
legend_fontsize = "6", #label names
ylog = 10,
ymin = 10,
yhash_marks = [100, 1000, 10000, 43200],
yhash_names = ["100", "1000", "10000", "43200"],
) + output_list]
