def frac_free_data(filename):
size = hintgc_format.get_column(filename, hintgc_format.heap_size)
hinted = hintgc_format.get_column(filename, hintgc_format.amount_hinted)
caught = hintgc_format.get_column(filename, hintgc_format.subject_reclaimed)
leaked = hintgc_format.get_column(filename, hintgc_format.followup_reclaimed)
tuples = zip(size, hinted, caught, leaked)
def denom(row):
return (max(float(row[2]),0)+max(float(row[3]),0))
def compute_row(row):
total = denom(row)
sub = max(float(row[2]),0)
fol = max(float(row[3]), 0)
if total > 0: # artifical limit to avoid bullshit data
return [sub/total, fol/total]
else:
return [0.0, 0.0]
# bin by size, then do that plot - closer to actually useful
percentages = [ [compute_row(row), row] for row in tuples]
fol = [row[0][1]*100 for row in percentages]
#print fol
if False:
def looks_like_garbage(item):
if float(item[1][1]) != 0:
if float(item[1][2])/float(item[1][1]) > .9 and int(item[1][3]) <= 30000:
return True
else:
return False
c = 0
print "Details"
for item in percentages:
if item[0][1]*100 > 20 and not looks_like_garbage(item):
c += 1
print item
print c
if True:
def looks_like_garbage(item):
if float(item[1][1]) != 0:
if int(item[1][3]) <= 100000000:
return True
else:
return False
c = 0
print "Details"
for item in percentages:
if item[0][1]*100 > 20 and not looks_like_garbage(item):
c += 1
print item
print c
return get_stats(fol)
def one_bench_data(f):
assert os.path.exists(f)
#print mb
heap_size = hintgc_format.get_column(f, hintgc_format.heap_size)
heap_size = [int(x) for x in heap_size]
#print heap_size
# they're only _mostly_ equal - fragementation (FIXME)
#assert_all_equal(heap_size)
size_map = { 33398784.0 : "31.8 MB", 24899584.0 : "23.7 MB", 92938240.0 : "88.6 MB", 193601536.0 : "184.6 MB", 59383808.0 : "56.6 MB", 780804096.0 : "744.6 MB", 27119616.0 : "25.9 MB", 29339648.0 : "28 MB" }
heap_size = size_map[numpy.mean(heap_size)]
def gc_flag(row):
return int(row[5])
flags = hintgc_format.get_column_pf(f, gc_flag)
assert_all_equal(flags);
assert flags[0] == 0
flags = hintgc_format.get_column_gc(f, gc_flag)
assert_all_equal(flags);
assert flags[0] == 1
pfruntime = hintgc_format.get_column_pf(f, hintgc_format.runtime)
pfruntime = [int(x) for x in pfruntime]
gcruntime = hintgc_format.get_column_gc(f, hintgc_format.runtime)
gcruntime = [int(x) for x in gcruntime]
#print pfruntime
#print gcruntime
gc = numpy.mean(gcruntime)
pf = numpy.mean(pfruntime)
return [gc, pf, heap_size]
def hist2d(gccsvfile, pfcsvfile, rootname, xselect):
ofile = open(rootname + ".dat", 'w')
gcbins = hintgc_format.bin_column(gccsvfile, xselect)
pfbins = hintgc_format.bin_column(pfcsvfile, xselect)
gckeysi = [int(i) for i in gcbins.keys()]
pfkeysi = [int(i) for i in pfbins.keys()]
a = hintgc_format.get_column(gccsvfile, xselect)
print_stats(a)
a = hintgc_format.get_column(pfcsvfile, xselect)
print_stats(a)
lowest = min( min(gckeysi), min(pfkeysi))
highest = max( max(gckeysi), max(pfkeysi))
for i in range(lowest, highest+1, 10):
key = str(i)
if key not in gcbins:
gcbins[key] = 0
if key not in pfbins:
pfbins[key] = 0
for i in range(250, highest+1, 10):
key = str(i)
gcval = gcbins[key]
pfval = pfbins[key]
ofile.write( str(key) + ' ' + str(gcval) + ' ' + str(pfval) + '\n')
with open(rootname + ".plt", 'w') as pltfile:
pltfile.write("set term epslatex\n")
pltfile.write("set output '"+rootname+".tex'\n")
pltfile.write("set ylabel \""+hintgc_format.labels[xselect]+"\"\n")
pltfile.write("set xlabel \"Count\"\n")
pltfile.write("set yrange [*:*]\n")
pltfile.write("plot \""+rootname+".dat\" using 2:1 title \"GC\" lt rgb \"red\", \""+rootname+".dat\" using 3:1 title \"PF\" lt rgb \"blue\"\n")
with open("generated/commands.sh", "a") as cmds:
cmds.write("gnuplot "+rootname+".plt && epstopdf "+rootname+".eps\n")
def format_time(num):
num = float(num)
s = '%2.2f' % num;
if s.startswith("0."):
s = " "+s
return s
rows = []
for mb in files:
def gc_flag(row):
return int(row[5])
pff = input_location + mb[1]
flags = hintgc_format.get_column(pff, gc_flag)
assert_all_equal(flags);
assert flags[0] == 0
# flags = hintgc_format.get_column(gcf, gc_flag)
# assert_all_equal(flags);
# assert flags[0] == 1
def get_stats(data):
data = [float(x) for x in data]
return [len(data), min(data), max(data), format_time(sum(data)/len(data)),
scipy.stats.scoreatpercentile(data, 50),
#scipy.stats.scoreatpercentile(data, 95),
#scipy.stats.scoreatpercentile(data, 90),
#scipy.stats.scoreatpercentile(data, 99),
#scipy.stats.scoreatpercentile(data, 99.9),
#scipy.stats.scoreatpercentile(data, 99.95),
return '%.2f' % num;
def format_int(num):
num = float(num)
s = '%d' % num;
return s
rows = []
if False:
def gc_flag(row):
return int(row[5])
# these data files are not mixed
pff = "../benchmarks/results/clang_build_pf_stats-release.csv"
gcf = "../benchmarks/results/clang_build_gc_stats-release.csv"
flags = hintgc_format.get_column(pff, gc_flag)
assert_all_equal(flags);
assert flags[0] == 0
flags = hintgc_format.get_column(gcf, gc_flag)
assert_all_equal(flags);
assert flags[0] == 1
scratch = hintgc_format.get_column(pff, hintgc_format.subject_reclaimed)
scratch = [int(x) for x in scratch]
reclaimed = sum(scratch)
scratch = hintgc_format.get_column(pff, hintgc_format.amount_hinted)
scratch = [int(x) for x in scratch]
hinted = sum(scratch)
hinted_a = scratch
input_location = sys.argv[1];
import os
assert os.path.exists(input_location)
config = sys.argv[2]
assert config in ["all", "basic", "opts"]
rows = []
for mb in files:
if os.path.exists(input_location + "edge-filtered-header/"):
f = input_location + "edge-filtered-header/" + mb[1]
else:
f = input_location + mb[1]
assert os.path.exists(f)
#print mb
heap_size = hintgc_format.get_column(f, hintgc_format.heap_size)
heap_size = [int(x) for x in heap_size]
#print heap_size
# they're only _mostly_ equal - fragementation (FIXME)
#assert_all_equal(heap_size)
size_map = { 33398784.0 : "31.8 MB", 24899584.0 : "23.7 MB", 92938240.0 : "88.6 MB", 193601536.0 : "184.6 MB", 59383808.0 : "56.6 MB", 780804096.0 : "744.6 MB", 27119616.0 : "25.9 MB", 29339648.0 : "28 MB" }
heap_size = size_map[numpy.mean(heap_size)]
def gc_flag(row):
return int(row[5])
flags = hintgc_format.get_column_pf(f, gc_flag)
while num >= 1000:
num = num / 1000
p = p + 1
return ("%.2f" % num) + " " + units[p]
rows = []
for mb in files:
def gc_flag(row):
return int(row[5])
# these data files are not mixed
pff = input_location + mb[1]
#gcf = "../benchmarks/results/spec-test-gc/" + mb[1]
flags = hintgc_format.get_column(pff, gc_flag)
assert_all_equal(flags);
assert flags[0] == 0
# flags = hintgc_format.get_column(gcf, gc_flag)
# assert_all_equal(flags);
# assert flags[0] == 1
scratch = hintgc_format.get_column(pff, hintgc_format.subject_reclaimed)
scratch = [int(x) for x in scratch]
reclaimed = sum(scratch)
scratch = hintgc_format.get_column(pff, hintgc_format.amount_hinted)
scratch = [int(x) for x in scratch]
hinted = sum(scratch)
hinted_a = scratch
