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#!/usr/bin/python
#######################################################
# Copyright (c) 2015, ArrayFire
# All rights reserved.
#
# This file is distributed under 3-clause BSD license.
# The complete license agreement can be obtained at:
# http://arrayfire.com/licenses/BSD-3-Clause
########################################################
from random import random
from time import time
from arrayfire import (array, randu)
import arrayfire as af
import sys
#alias range / xrange because xrange is faster than range in python2
try:
frange = xrange #Python2
except NameError:
frange = range #Python3
def calc_pi_device(samples):
x = randu(samples)
y = randu(samples)
return 4 * af.sum((x * x + y * y) < 1) / samples
# Having the function outside is faster than the lambda inside
def in_circle(x, y):
return (x*x + y*y) < 1
def calc_pi_host(samples):
count = sum(1 for k in frange(samples) if in_circle(random(), random()))
return 4 * float(count) / samples
def bench(calc_pi, samples=1000000, iters=25):
func_name = calc_pi.__name__[8:]
print("Monte carlo estimate of pi on %s with %d million samples: %f" % \
(func_name, samples/1e6, calc_pi(samples)))
start = time()
for k in frange(iters):
calc_pi(samples)
end = time()
print("Average time taken: %f ms" % (1000 * (end - start) / iters))
if __name__ == "__main__":
if (len(sys.argv) > 1):
af.set_device(int(sys.argv[1]))
af.info()
bench(calc_pi_device)
bench(calc_pi_host)
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