def main():
conf = Conf()
usf_file = open_sample_file(conf.ifile_name, conf.line_size)
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
usf_file.close()
cache_size_range = default_range_func()
line_size = 64
cache_size_range = map(lambda x: x / line_size, cache_size_range)
pref_pcs = prefetchable_pcs(burst_hists)
rdist_hist = rdist_hist_original(burst_hists)
mr = lrumodel.miss_ratio_range([rdist_hist], cache_size_range, filtered_rdist_hist_list = [rdist_hist])
rdist_hist_w_pf = rdist_hist_after_prefetching(burst_hists, pref_pcs)
mr_w_pf = lrumodel.miss_ratio_range([rdist_hist], cache_size_range, filtered_rdist_hist_list = [rdist_hist_w_pf])
print mr
print mr_w_pf
def main():
conf = Conf()
usf_file = open_sample_file(conf.ifile_name, conf.line_size)
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
usf_file.close()
hist = generate_sdist_hist(burst_hists)
data = hist.items()
data.sort(key=lambda x: x[0])
l1_sd_samples = 0
l2_sd_samples = 0
l3_sd_samples = 0
mem_sd_samples = 0
non_l1_sd_samples = 0
total_sd_samples = 0
for (sd, count) in data:
# print "%i %i" % (sd * conf.line_size, count)
total_sd_samples += count
if sd < 1024: # 1024 number of cache lines in 64kB L1 cache
l1_sd_samples += count
continue
elif sd < 8192:
l2_sd_samples += count
elif sd < 98304:
l3_sd_samples += count
else:
mem_sd_samples += count
non_l1_sd_samples += count
l1_bound_samples = (float(l1_sd_samples) / float(total_sd_samples) * 100)
l2_bound_samples = (float(l2_sd_samples) / float(non_l1_sd_samples) * 100)
l3_bound_samples = (float(l3_sd_samples) / float(non_l1_sd_samples) * 100)
mem_bound_samples = (float(mem_sd_samples) / float(non_l1_sd_samples) *
100)
non_l1_bound_samples = (float(non_l1_sd_samples) /
float(total_sd_samples) * 100)
print "L1 %.2f %% of total" % (l1_bound_samples)
print "L2 %.2f %% of %.2f %%" % (l2_bound_samples, non_l1_bound_samples)
print "L3 %.2f %% of %.2f %%" % (l3_bound_samples, non_l1_bound_samples)
print "Memory %.2f %% of %.2f %%" % (mem_bound_samples,
non_l1_bound_samples)
def main():
conf = Conf()
usf_file = open_sample_file(conf.ifile_name, conf.line_size)
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
usf_file.close()
hist = generate_sdist_hist(burst_hists)
data = hist.items()
data.sort(key=lambda x: x[0])
x_values = map(lambda (x, y): x * conf.line_size, data)
y_values = map(lambda (x, y): y, data)
if not x_values:
print >> sys.stderr, "WARNING: Filter result is empty. Nothing to plot."
sys.exit(0)
if x_values[0] == 0:
print >> sys.stderr, "WARNING: Not showing stack distance 0 in hist."
print >> sys.stderr, "sdist: 0, count: %d" % (y_values[0])
x_values = x_values[1:]
y_values = y_values[1:]
if not x_values:
print >> sys.stderr, "WARNING: Nothing to plot. Exiting."
sys.exit(0)
# plot the histogram
pyplot.hold(True)
pyplot.title("Stack distance histogram")
pyplot.ylabel("Samples")
pyplot.xlabel("Stack distance (bytes)")
pyplot.yscale('log', basey=10)
pyplot.xscale('log', basex=2)
pyplot.bar(x_values, y_values)
for marker in conf.markers:
print "Marker: %i" % marker
pyplot.axvline(marker)
pyplot.axis([1, float(max(x_values)), 1, float(max(y_values))])
pyplot.hold(False)
pyplot.show()
def main():
conf = Conf()
usf_file = open_sample_file(conf.ifile_name, conf.line_size)
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
usf_file.close()
hist = generate_sdist_hist(burst_hists)
data = hist.items()
data.sort(key=lambda x: x[0])
x_values = map(lambda (x, y): x * conf.line_size, data)
y_values = map(lambda (x, y): y, data)
if not x_values:
print >> sys.stderr, "WARNING: Filter result is empty. Nothing to plot."
sys.exit(0)
if x_values[0] == 0:
print >> sys.stderr, "WARNING: Not showing stack distance 0 in hist."
print >> sys.stderr, "sdist: 0, count: %d" % (y_values[0])
x_values = x_values[1:]
y_values = y_values[1:]
if not x_values:
print >> sys.stderr, "WARNING: Nothing to plot. Exiting."
sys.exit(0)
# plot the histogram
pyplot.hold(True)
pyplot.title("Stack distance histogram")
pyplot.ylabel("Samples")
pyplot.xlabel("Stack distance (bytes)")
pyplot.yscale('log', basey = 10)
pyplot.xscale('log', basex = 2)
pyplot.bar(x_values, y_values)
for marker in conf.markers:
print "Marker: %i" % marker
pyplot.axvline(marker);
pyplot.axis([ 1, float(max(x_values)), 1, float(max(y_values)) ])
pyplot.hold(False)
pyplot.show()
def main():
conf = Conf()
usf_file = open_sample_file(conf.ifile_name, conf.line_size)
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
usf_file.close()
hist = generate_sdist_hist(burst_hists)
data = hist.items()
data.sort(key=lambda x: x[0])
l1_sd_samples = 0
l2_sd_samples = 0
l3_sd_samples = 0
mem_sd_samples = 0
non_l1_sd_samples = 0
total_sd_samples = 0
for (sd, count) in data:
# print "%i %i" % (sd * conf.line_size, count)
total_sd_samples += count
if sd < 1024: # 1024 number of cache lines in 64kB L1 cache
l1_sd_samples += count
continue
elif sd < 8192:
l2_sd_samples += count
elif sd < 98304:
l3_sd_samples += count
else:
mem_sd_samples += count
non_l1_sd_samples += count
l1_bound_samples = (float(l1_sd_samples)/float(total_sd_samples)*100)
l2_bound_samples = (float(l2_sd_samples)/float(non_l1_sd_samples)*100)
l3_bound_samples = (float(l3_sd_samples)/float(non_l1_sd_samples)*100)
mem_bound_samples = (float(mem_sd_samples)/float(non_l1_sd_samples)*100)
non_l1_bound_samples = (float(non_l1_sd_samples)/float(total_sd_samples) * 100)
print "L1 %.2f %% of total"%(l1_bound_samples)
print "L2 %.2f %% of %.2f %%"%(l2_bound_samples, non_l1_bound_samples)
print "L3 %.2f %% of %.2f %%"%(l3_bound_samples, non_l1_bound_samples)
print "Memory %.2f %% of %.2f %%"%(mem_bound_samples, non_l1_bound_samples)
def main():
conf = Conf()
usf_file = open_sample_file(conf.ifile_name, conf.line_size)
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
usf_file.close()
hist = generate_rdist_hist(burst_hists)
data = hist.items()
data.sort(key=lambda x: x[0])
#Print reuse distance histogram distribution
f = open('.temp.csv', 'w')
for (rdist, count) in data:
value = rdist, count
s = str(value)
f.write(s)
f.write('\n')
x_values = map(lambda (x, y): x, data)
y_values = map(lambda (x, y): y, data)
if not x_values:
print >> sys.stderr, "WARNING: Filter result is empty. Nothing to plot."
sys.exit(0)
if not x_values:
print >> sys.stderr, "WARNING: Nothing to plot. Exiting."
sys.exit(0)
# plot the histogram
pyplot.hold(True)
pyplot.title("Reuse distance distance histogram")
pyplot.ylabel("Samples")
pyplot.xlabel("Reuse distance (accesses)")
pyplot.yscale('log', basey = 10)
pyplot.xscale('log', basex = 2)
pyplot.bar(x_values, y_values)
pyplot.axis([ 1, float(max(x_values)), 1, float(max(y_values)) ])
pyplot.hold(False)
pyplot.show()
def main():
conf = Conf()
usf_file = open_sample_file(conf.ifile_name, conf.line_size)
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
usf_file.close()
hist = generate_rdist_hist(burst_hists)
data = hist.items()
data.sort(key=lambda x: x[0])
#Print reuse distance histogram distribution
f = open('.temp.csv', 'w')
for (rdist, count) in data:
value = rdist, count
s = str(value)
f.write(s)
f.write('\n')
x_values = map(lambda (x, y): x, data)
y_values = map(lambda (x, y): y, data)
if not x_values:
print >> sys.stderr, "WARNING: Filter result is empty. Nothing to plot."
sys.exit(0)
if not x_values:
print >> sys.stderr, "WARNING: Nothing to plot. Exiting."
sys.exit(0)
# plot the histogram
pyplot.hold(True)
pyplot.title("Reuse distance distance histogram")
pyplot.ylabel("Samples")
pyplot.xlabel("Reuse distance (accesses)")
pyplot.yscale('log', basey=10)
pyplot.xscale('log', basex=2)
pyplot.bar(x_values, y_values)
pyplot.axis([1, float(max(x_values)), 1, float(max(y_values))])
pyplot.hold(False)
pyplot.show()
def main():
conf = Conf()
listing = os.listdir(conf.path)
cache_size_range = default_range_func()
win_count = 0
mr = {}
mr_w_pf = {}
pref_pcs_win = {}
full_pc_stride_hist = {}
global_pc_fwd_sdist_hist = {}
global_pc_sdist_hist = {}
global_pc_corr_hist = {}
global_pc_recur_hist = {}
global_prefetchable_pcs = []
global_pc_smptrace_hist = {}
if not conf.num_samples is None:
num_sample_files = len(listing)
files_required = math.ceil(float(conf.num_samples) / float(1200)) + 1 # 1200 is the number of samples per file
files_sapcing = int(math.ceil(float(num_sample_files) / float(files_required)))
print >> sys.stderr, "files spacing: %d"%(files_sapcing)
if files_sapcing == 0:
files_sapcing = 1
file_no = 0
listing = []
while file_no < num_sample_files:
file_name = "sample."+str(file_no)
listing.append(file_name)
file_no += files_sapcing
for infile in listing:
infile = conf.path + infile
usf_file = open_sample_file(infile, conf.line_size)
if usf_file == None:
continue
try:
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
except IOError, e:
continue
usf_file.close()
pref_pcs_sdist_recur_list = prefetchable_pcs(burst_hists, conf)
pref_pcs = pref_pcs_sdist_recur_list[0]
pc_sdist_hist = pref_pcs_sdist_recur_list[1]
pc_recur_hist = pref_pcs_sdist_recur_list[2]
pc_fwd_sdist_hist = pref_pcs_sdist_recur_list[3]
build_global_prefetchable_pcs(global_prefetchable_pcs, pref_pcs)
pc_corr_hist = burst_hists[0][4]
build_global_pc_corr_hist(global_pc_corr_hist, pc_corr_hist)
build_global_pc_fwd_sdist_recur_hist(global_pc_fwd_sdist_hist, global_pc_recur_hist, pc_fwd_sdist_hist, pc_recur_hist, global_pc_sdist_hist, pc_sdist_hist)
build_full_pc_stride_hist(burst_hists, full_pc_stride_hist)
pc_smptrace_hist = burst_hists[0][6]
ins_trace_analysis.add_trace_to_global_pc_smptrace_hist(global_pc_smptrace_hist, pc_smptrace_hist)
def main():
ins_src_regs_dict = {}
ins_dst_regs_dict = {}
ins_tags_dict = {}
branch_dict = {}
routine_BB_dict = {}
# information maps for Memory operations
ins_base_reg_dict = {}
ins_mem_dis_dict = {}
ins_idx_reg_dict = {}
ins_mem_scale_dict = {}
global_prefetchable_pcs = []
global_pc_smptrace_hist = {}
global_pc_stride_hist = {}
conf = Conf()
if not conf.hex_address == None:
delinq_load_addr = int(conf.hex_address, 16)
else:
delinq_load_addr = int(conf.dec_address, 10)
delinq_load_address_list = get_delinq_load_address_list(conf)
if delinq_load_address_list == None:
delinq_load_address_list = [delinq_load_addr]
listing = os.listdir(conf.path)
if not conf.num_samples is None:
num_sample_files = len(listing)
files_required = math.ceil(float(conf.num_samples) / float(1200)) + 1 # 1200 is the number of samples per file
files_sapcing = int(math.ceil(float(num_sample_files) / float(files_required)))
print >> sys.stderr, "files spacing: %d"%(files_sapcing)
if files_sapcing == 0:
files_sapcing = 1
file_no = 0
listing = []
while file_no < num_sample_files:
file_name = "sample."+str(file_no)
listing.append(file_name)
file_no += files_sapcing
for infile in listing:
infile = conf.path + infile
usf_file = open_sample_file(infile, conf.line_size)
if usf_file == None:
continue
try:
burst_hists = utils.usf_read_events(usf_file,
line_size=conf.line_size,
filter=conf.filter)
except IOError, e:
continue
usf_file.close()
for (pc_rdist_hist, pc_stride_hist, pc_freq_hist, pc_time_hist, pc_corr_hist, pc_fwd_rdist_hist, pc_smptrace_hist) in burst_hists:
continue
ins_trace_ptr_nobj_analysis.add_trace_to_global_pc_smptrace_hist(global_pc_smptrace_hist, pc_smptrace_hist)
ins_trace_ptr_nobj_analysis.add_to_pc_stride_hist(pc_stride_hist, global_pc_stride_hist)
