Python 分布式计算模块：Parallel
jopen
11年前
Parallel Python是一个Python模块，它提供了Python代码的在SMP（系统有多个处理器或内核）和集群（计算机通过网络连接）上并行执行的机制。能够将计算压力分布到多核CPU或集群的多台计算机上，能够非常方便的在内网中搭建一个自组织的分布式计算平台。先从多核计算开始，普通的Python应用程序只能够使用一个CPU进程，而通过Parallel Python能够很方便的将计算扩展到多个CPU进程。
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.)
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