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sdistprint.py
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sdistprint.py
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#!/usr/bin/python
import sys
import math
import os
from optparse import OptionParser
from uart.hist import Hist
import uart.sample_filter as sample_filter
import pyusf
import lrumodel
import utils
import missratio
__version__ = "$Revision$"
class Conf:
def __init__(self):
parser = OptionParser("usage: %prog [OPTIONS...] INFILE")
parser.add_option("-l", "--line-size",
type="int", default="64",
dest="line_size",
help="Use a specific line size.")
parser.add_option("-f", "--filter",
type="str", default="all()",
dest="filter",
help="Filter for events to display in histogram.")
parser.add_option("--help-filters",
action="callback", callback=self.help_filters,
help="Display help about the filter language.")
(opts, args) = parser.parse_args()
if opts.line_size <= 0 or \
opts.line_size & (opts.line_size - 1) != 0:
print >> sys.stderr, "Invalid line size specified."
sys.exit(1)
if len(args) == 0:
print >> sys.stderr, "No input file specified."
sys.exit(1)
self.filter = sample_filter.from_str(opts.filter)
self.ifile_name = args[0]
self.line_size = opts.line_size
def help_filters(self, option, opt, value, parser):
sample_filter.usage()
sys.exit(0)
def pow2(x):
return int(math.pow(2, x))
def pow2_range(l, u):
return map(pow2, range(l, u))
def default_range_func():
return pow2_range(10, 24)
def open_sample_file(file_name, line_size):
try:
usf_file = pyusf.Usf()
usf_file.open(file_name)
except IOError, e:
print >> sys.stderr, "Error: %s" % str(e)
sys.exit(1)
if usf_file.header.flags & pyusf.USF_FLAG_TRACE:
print >> sys.stderr, "Error: Specified file is a trace."
sys.exit(1)
if not usf_file.header.line_sizes & line_size:
print >> sys.stderr, \
"Eror: Specified line size does not exist in sample file."
sys.exit(1)
return usf_file
#def generate_sdist_hist(burst_hists):
# hist = {}
# for (rdists, filtered_rdists) in burst_hists:
# r2s = lrumodel.lru_sdist(rdists)
# for (rdist, count) in filtered_rdists.items():
# sdist = r2s[rdist]
# hist[sdist] = hist.get(sdist, 0) + count
# return hist
def generate_sdist_hist(rdist_hist):
hist = {}
r2s = lrumodel.lru_sdist(rdist_hist)
for (rdist, count) in rdist_hist.items():
sdist = r2s[rdist]
hist[sdist] = hist.get(sdist, 0) + count
return hist
def print_stride_info(burst_hists):
for (pc_rdist_hist, pc_stride_hist, pc_freq_hist, pc_time_hist) in burst_hists:
comm_pc = pc_freq_hist.items()
comm_pc.sort(key=lambda x: x[1], reverse=True)
for (pc, count) in comm_pc:
print"pc: %lx count: %d\n"%(pc, count)
stride_cnt_list = pc_stride_hist[pc].items()
stride_cnt_list.sort(key=lambda x: x[1], reverse=True)
for (stride, count) in stride_cnt_list:
print"stride: %d, %d\n"%(stride, count)
def rdist_hist_original(burst_hists):
hist = {}
for (pc_rdist_hist, pc_stride_hist, pc_freq_hist, pc_time_hist) in burst_hists:
for (pc, rdist_hist) in pc_rdist_hist.items():
for (rdist, count) in rdist_hist.items():
hist[rdist] = hist.get(rdist, 0) + count
return hist
def reduce_stride_hist(pc_stride_hist):
hist = {}
c = 0
avg_stride_count = 0
for (pc, stride_hist) in pc_stride_hist.items():
for (stride, count) in stride_hist.items():
if stride == 0 or count == 1:
continue
avg_stride_count += count
c += 1
avg_stride_count = math.floor(float(avg_stride_count) / float(c))
for (pc, stride_hist) in pc_stride_hist.items():
for (stride, count) in stride_hist.items():
if stride == 0 or count == 1: #avg_stride_count: # 10:
continue
if not pc in hist:
hist[pc]= {}
hist[pc][stride] = count
return hist
def rdist_hist_after_prefetching(burst_hists, pref_pcs):
hist = {}
for (pc_rdist_hist, pc_stride_hist, pc_freq_hist, pc_time_hist) in burst_hists:
# comm_pc = pc_freq_hist.items()
# comm_pc.sort(key=lambda x: x[1], reverse=True)
# reduced_pc_stride_hist = reduce_stride_hist(pc_stride_hist)
# total_samples = 0
# for (pc, count) in comm_pc:
# total_samples += count
# for (pc, count) in comm_pc:
# if pc in reduced_pc_stride_hist:
# stride_hist = reduced_pc_stride_hist[pc]
#if len(stride_hist) <= 2:
# if len(stride_hist) == 1:
# pref_pcs.append(pc)
for pc in pref_pcs:
if len(pc_stride_hist[pc]) != 1:
pref_pcs.remove(pc)
for (pc, rdist_hist) in pc_rdist_hist.items():
for (rdist, count) in rdist_hist.items():
if pref_pcs.count(pc) == 0:
hist[rdist] = hist.get(rdist, 0) + count
if len(hist) == 0:
for (pc, rdist_hist) in pc_rdist_hist.items():
for (rdist, count) in rdist_hist.items():
hist[rdist] = 0
return hist
def generate_per_pc_sdist_recurrence_hist(burst_hists):
pc_sdist_hist = {}
pc_recur_hist = {}
for (pc_rdist_hist, pc_stride_hist, pc_freq_hist, pc_time_hist) in burst_hists:
rdist_hist = rdist_hist_original(burst_hists)
r2s = lrumodel.lru_sdist(rdist_hist)
for (pc, rdist_hist) in pc_rdist_hist.items():
if not pc in pc_sdist_hist:
pc_sdist_hist[pc] = {}
for (rdist, count) in rdist_hist.items():
sd = int(round(r2s[rdist]))
pc_sdist_hist[pc][sd] = pc_sdist_hist.get(sd, 0) + count
for (pc, time_hist) in pc_time_hist.items():
if not pc in pc_recur_hist:
pc_recur_hist[pc] = {}
for (recur, count) in time_hist.items():
if not recur in r2s:
recur_c = min(r2s.keys(), key=lambda k: abs(k-recur))
# print"recur %d -> %d"%(recur, recur_c)
recur = recur_c
sd = int(round(r2s[recur]))
pc_recur_hist[pc][sd] = pc_recur_hist.get(sd, 0) + count
return [pc_sdist_hist, pc_recur_hist]
def prefetchable_pcs(burst_hists):
sdist_recur_list = generate_per_pc_sdist_recurrence_hist(burst_hists)
pc_sdist_hist = sdist_recur_list[0]
pc_recur_hist = sdist_recur_list[1]
pref_pcs = []
for (pc, sdist_hist) in pc_sdist_hist.items():
if max(sdist_hist.keys()) > 1024 and max(pc_recur_hist[pc].keys()) < 512:
pref_pcs.append(pc)
return pref_pcs
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
# print_stride_info(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:
# total_sd_samples += count
# if sd < 512: # 512 number of cache lines in 32kB 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 bound memory accesses %.2f %% of total"%(l1_bound_samples)
# print "L2 bound memory accesses %.2f %% of %.2f %%"%(l2_bound_samples, non_l1_bound_samples)
# print "L3 bound memory accesses %.2f %% of %.2f %%"%(l3_bound_samples, non_l1_bound_samples)
# print "Memory bound memory accesses %.2f %% of %.2f %%"%(mem_bound_samples, non_l1_bound_samples)
if __name__ == "__main__":
main()