测试python的并行模块Parallel Python的效率

蒦嗳伱

　　未使用pp模块的代码执行时间测试:
　　下面的代码计算小于等于n的质数之和
# sum_primes_without_pp.pyimport math, sys, timedef isprime(n):"""Returns True if n is prime and False otherwise"""if not isinstance(n, int):raise TypeError("argument passed to is_prime is not of 'int' type")if n < 2:return Falseif n == 2:return Truemax = int(math.ceil(math.sqrt(n)))i = 2while i <= max:if n % i == 0:return Falsei += 1return Truedef sum_primes(n):"""Calculates sum of all primes below given integer n"""return sum([x for x in xrange(2,n) if isprime(x)])start_time = time.time()inputs = (100000, 100100, 100200, 100300, 100400, 100500, 100600, 100700)for input in inputs:print "Sum of primes below", input, "is", sum_primes(input)print "Time elapsed: ", time.time() - start_time, "s"　　
测试结果:
　　Sum of primes below 100000 is 454396537
Sum of primes below 100100 is 454996777
Sum of primes below 100200 is 455898156
Sum of primes below 100300 is 456700218
Sum of primes below 100400 is 457603451
Sum of primes below 100500 is 458407033
Sum of primes below 100600 is 459412387
Sum of primes below 100700 is 460217613
Time elapsed: 3.95300006866 s

　　下面的代码使用并行模块实现:
#!/usr/bin/python# File: sum_primes.py# Author: VItalii Vanovschi# Desc: This program demonstrates parallel computations with pp module# It calculates the sum of prime numbers below a given integer in parallel# Parallel Python Software: http://www.parallelpython.comimport math, sys, timeimport ppdef isprime(n):"""Returns True if n is prime and False otherwise"""if not isinstance(n, int):raise TypeError("argument passed to is_prime is not of 'int' type")if n < 2:return Falseif n == 2:return Truemax = int(math.ceil(math.sqrt(n)))i = 2while i <= max:if n % i == 0:return Falsei += 1return Truedef sum_primes(n):"""Calculates sum of all primes below given integer n"""return sum([x for x in xrange(2,n) if isprime(x)])print """Usage: python sum_primes.py [ncpus][ncpus] - the number of workers to run in parallel, if omitted it will be set to the number of processors in the system"""# tuple of all parallel python servers to connect withppservers = ()#ppservers = ("10.0.0.1",)if len(sys.argv) > 1:ncpus = int(sys.argv[1])# Creates jobserver with ncpus workersjob_server = pp.Server(ncpus, ppservers=ppservers)else:# Creates jobserver with automatically detected number of workersjob_server = pp.Server(ppservers=ppservers)print "Starting pp with", job_server.get_ncpus(), "workers"# Submit a job of calulating sum_primes(100) for execution. # sum_primes - the function# (100,) - tuple with arguments for sum_primes# (isprime,) - tuple with functions on which function sum_primes depends# ("math",) - tuple with module names which must be imported before sum_primes execution# Execution starts as soon as one of the workers will become availablejob1 = job_server.submit(sum_primes, (100,), (isprime,), ("math",))# Retrieves the result calculated by job1# The value of job1() is the same as sum_primes(100)# If the job has not been finished yet, execution will wait here until result is availableresult = job1()print "Sum of primes below 100 is", resultstart_time = time.time()# The following submits 8 jobs and then retrieves the resultsinputs = (100000, 100100, 100200, 100300, 100400, 100500, 100600, 100700)jobs = [(input, job_server.submit(sum_primes,(input,), (isprime,), ("math",))) for input in inputs]for input, job in jobs:print "Sum of primes below", input, "is", job()print "Time elapsed: ", time.time() - start_time, "s"job_server.print_stats()　　
测试结果如下:
　　Starting pp with 2 workers
Sum of primes below 100 is 1060
Sum of primes below 100000 is 454396537
Sum of primes below 100100 is 454996777
Sum of primes below 100200 is 455898156
Sum of primes below 100300 is 456700218
Sum of primes below 100400 is 457603451
Sum of primes below 100500 is 458407033
Sum of primes below 100600 is 459412387
Sum of primes below 100700 is 460217613
Time elapsed: 1.95300006866 s
Job execution statistics:
job count | % of all jobs | job time sum | time per job | job server
9 | 100.00 | 3.9060 | 0.434000 | local
Time elapsed since server creation 1.95300006866
可以发现同样的任务,节约的时间很多,效率提高100%!