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#!/usr/bin/env python
import os
import time
import string
import StringIO
import tempfile
import numpy
import sqlite3
from matplotlib import pyplot
from matplotlib import pylab
class Statistics:
def __init__(self):
print("Initializing %s" % (self.__class__))
self.results = {}
pass
def store(self, key, value):
try:
self.results[key] = value
except:
return False
return True
def append(self, key, value):
try:
self.results[key].append(value)
except:
return False
return True
def retrieve(self):
return self.results[self.name]
def get_numpy(self, key):
data = self.results[key]
xlist = []
ylist = []
for x, y in data:
xlist.append(x)
ylist.append(y)
x = numpy.array(xlist)
y = numpy.array(ylist)
return x, y
def plot(self):
pass
class Stopwatch:
def __init__(self):
self.start_time = 0.0
self.stop_time = 0.0
def start(self):
self.start_time = time.time()
def stop(self):
self.stop_time = time.time()
def now(self):
return (time.time() - self.start_time)
def result(self):
return (self.stop_time - self.start_time)
class Sequencial_test(Statistics):
def __init__(self, size=1):
'''
size in megabytes
bufsiz in bytes
mode is 'buffered' or 'unbuffered'
async is True or False
'''
Statistics.__init__(self)
Statistics.store(self, 'buffered_sync', [])
Statistics.store(self, 'buffered_async', [])
Statistics.store(self, 'unbuffered_sync', [])
Statistics.store(self, 'unbuffered_async', [])
self.MEGABYTE = 1024000
self.size = size
self.timer = Stopwatch()
self.random_source = os.urandom(self.MEGABYTE * 10)
self.prefix='sequencial_test_'
self.path_tests = os.path.join(os.curdir, 'tests')
self.path_results = os.path.join(os.curdir, 'results')
if not os.path.exists(self.path_tests):
os.mkdir(self.path_tests)
if not os.path.exists(self.path_results):
os.mkdir(self.path_results)
def __del__(self):
if os.path.exists(self.filename):
print('deleting %s' % (self.filename))
os.remove(os.path.join(self.filename))
def stress_test_wrapper(self, iter_max):
self.stress_buffered_sync(iter_max)
self.stress_buffered_async(iter_max)
self.stress_unbuffered_sync(iter_max)
self.stress_unbuffered_async(iter_max)
def stress_buffered_sync(self, iter_max=1):
print("Synchronous buffered I/O")
for i in range(iter_max):
print("\tTest: %d of %d" % (i+1, iter_max))
self.buffered_sync()
def stress_buffered_async(self, iter_max=1):
print("Asynchronous buffered I/O")
for i in range(iter_max):
print("\tTest: %d of %d" % (i+1, iter_max))
self.buffered_async()
def stress_unbuffered_sync(self, iter_max=1):
print("Synchronous unbuffered I/O")
for i in range(iter_max):
print("\tTest: %d of %d" % (i+1, iter_max))
self.unbuffered_sync()
def stress_unbuffered_async(self, iter_max=1):
print("Asynchronous unbuffered I/O")
for i in range(iter_max):
print("\tTest: %d of %d" % (i+1, iter_max))
self.unbuffered_async()
def buffered_sync(self):
Statistics.append(self,'buffered_sync', self.write_out(size=self.size))
def buffered_async(self):
Statistics.append(self, 'buffered_async', self.write_out(size=self.size, async=True))
def buffered_stepping(self):
pass
def unbuffered_sync(self):
Statistics.append(self, 'unbuffered_sync', self.write_out(size=self.size, mode='unbuffered'))
def unbuffered_async(self):
Statistics.append(self, 'unbuffered_async', self.write_out(size=self.size, mode='unbuffered', async=True))
def unbuffered_stepping(self):
pass
def write_out(self, size, bufsiz=1024000, mode='buffered', async=False):
size = size * self.MEGABYTE
temp = tempfile.NamedTemporaryFile(dir=self.path_tests, prefix=self.prefix, delete=False)
self.filename = temp.name
outfile = file(self.filename, 'wb')
total_bytes = 0
self.timer.start()
while total_bytes <= size:
try:
source = StringIO.StringIO(self.random_source)
if mode == 'buffered':
buf = source.read(bufsiz)
else:
buf = source.read()
outfile.write(buf)
if not async:
outfile.flush()
os.fsync(outfile)
total_bytes += len(buf)
rate_current = (total_bytes / self.timer.now() / 1024 / 1024)
source.close()
'''
if mode == 'buffered':
print("Buf:%d Sz:%d R:%0.2f Te:%0.4f\r" % (bufsiz, size, rate_current, self.timer.now())),
else:
print("Sz:%d R:%0.2f Te:%0.4f\r" % (size, rate_current, self.timer.now())),
'''
except:
print('Failed')
self.timer.stop()
return False
outfile.close()
self.timer.stop()
rate = (total_bytes / self.timer.result() / 1024 / 1024)
elapsed = self.timer.result()
#print('TR:%0.4fs R:%0.2f MB/s' % (self.timer.result(), rate))
os.remove(self.filename)
return rate, elapsed
def read_in(self):
pass
if __name__ == "__main__":
size_steps = [ 1, 4, 8 ]
buffer_steps = [ 512000, 1024000, 4096000 ]
iter_max=10
for size in size_steps:
print("### %dMB ####" % (size))
sequence_test = Sequencial_test(size)
sequence_test.stress_buffered_sync(iter_max)
sequence_test.stress_buffered_async(iter_max)
sequence_test.stress_unbuffered_sync(iter_max)
sequence_test.stress_unbuffered_async(iter_max)
for k in sequence_test.results:
print('Plotting %s' % (k))
rate, elapsed = sequence_test.get_numpy(k)
rate_mean = numpy.repeat(numpy.mean(rate), rate.size, 0)
#rate_average = numpy.repeat(numpy.average(rate), rate.size, 0)
elapsed_mean = numpy.repeat(numpy.mean(elapsed), elapsed.size, 0)
#elapsed_average = numpy.repeat(numpy.average(elapsed), elapsed.size, 0)
print("Rate mean: %f" % (numpy.mean(rate_mean)))
print("Elapsed mean: %f" % (numpy.mean(elapsed_mean)))
pyplot.figure(1)
pyplot.subplot(211)
pyplot.title(k)
pyplot.grid(True)
pyplot.xlabel('Iteration')
pyplot.ylabel('Rate (MB/s)')
pyplot.plot(rate)
#pyplot.plot(rate_average)
pyplot.plot(rate_mean)
pyplot.subplot(212)
pyplot.grid(True)
pyplot.xlabel('Iteration')
pyplot.ylabel('Time to Write')
pyplot.plot(elapsed)
#pyplot.plot(elapsed_average)
pyplot.plot(elapsed_mean)
pyplot.savefig(os.path.join(sequence_test.path_results, string.join([k, str(sequence_test.size)], sep='_')))
pyplot.close()
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