Python 分布式計算模塊：Parallel

Parallel Python是一個Python模塊，它提供了Python代碼的在SMP（系統有多個處理器或內核）和集群（計算機通過網絡連接）上并行執行的機制。能夠將計算壓力分布到多核CPU或集群的多臺計算機上，能夠非常方便的在內網中搭建一個自組織的分布式計算平臺。先從多核計算開始，普通的Python應用程序只能夠使用一個CPU進程，而通過Parallel Python能夠很方便的將計算擴展到多個CPU進程。

特性:

• Parallel execution of python code on SMP and clusters
• Easy to understand and implement job-based parallelization technique (easy to convert serial application in parallel)
• Automatic detection of the optimal configuration (by default the number of worker processes is set to the number of effective processors)
• Dynamic processors allocation (number of worker processes can be changed at runtime)
• Low overhead for subsequent jobs with the same function (transparent caching is implemented to decrease the overhead)
• Dynamic load balancing (jobs are distributed between processors at runtime)
• Fault-tolerance (if one of the nodes fails tasks are rescheduled on others)
• Auto-discovery of computational resources
• Dynamic allocation of computational resources (consequence of auto-discovery and fault-tolerance)
• SHA based authentication for network connections
• Cross-platform portability and interoperability (Windows, Linux, Unix, Mac OS X)
• Cross-architecture portability and interoperability (x86, x86-64, etc.)
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Example #1: sum_primes.py  

#!/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.com

import math, sys, time
import pp

def 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 False
    if n == 2:
        return True
    max = int(math.ceil(math.sqrt(n)))
    i = 2
    while i <= max:
        if n % i == 0:
            return False
        i += 1
    return True

def 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 with
ppservers = ()
#ppservers = ("10.0.0.1",)

if len(sys.argv) > 1:
    ncpus = int(sys.argv[1])
    # Creates jobserver with ncpus workers
    job_server = pp.Server(ncpus, ppservers=ppservers)
else:
    # Creates jobserver with automatically detected number of workers
    job_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 available
job1 = 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 available
result = job1()

print "Sum of primes below 100 is", result

start_time = time.time()

# The following submits 8 jobs and then retrieves the results
inputs = (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()

# Parallel Python Software: http://www.parallelpython.com




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