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Python 多处理只使用一个内核

转载 作者:太空狗 更新时间:2023-10-29 18:09:11 36 4
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我正在尝试来自 standard python documentation 的代码片段学习如何使用多处理模块。代码粘贴在此消息的末尾。我在四核机器上的 Ubuntu 11.04 上使用 Python 2.7.1(根据系统监视器,由于超线程,它给了我八个内核)

问题:所有工作负载似乎都被安排到一个核心上,尽管有多个进程已启动,但该核心的利用率接近 100%。有时所有工作负载都会迁移到另一个核心,但工作负载永远不会在它们之间分配。

知道为什么会这样吗?

最好的问候,

保罗

#
# Simple example which uses a pool of workers to carry out some tasks.
#
# Notice that the results will probably not come out of the output
# queue in the same in the same order as the corresponding tasks were
# put on the input queue. If it is important to get the results back
# in the original order then consider using `Pool.map()` or
# `Pool.imap()` (which will save on the amount of code needed anyway).
#
# Copyright (c) 2006-2008, R Oudkerk
# All rights reserved.
#

import time
import random

from multiprocessing import Process, Queue, current_process, freeze_support

#
# Function run by worker processes
#

def worker(input, output):
for func, args in iter(input.get, 'STOP'):
result = calculate(func, args)
output.put(result)

#
# Function used to calculate result
#

def calculate(func, args):
result = func(*args)
return '%s says that %s%s = %s' % \
(current_process().name, func.__name__, args, result)

#
# Functions referenced by tasks
#

def mul(a, b):
time.sleep(0.5*random.random())
return a * b

def plus(a, b):
time.sleep(0.5*random.random())
return a + b


def test():
NUMBER_OF_PROCESSES = 4
TASKS1 = [(mul, (i, 7)) for i in range(500)]
TASKS2 = [(plus, (i, 8)) for i in range(250)]

# Create queues
task_queue = Queue()
done_queue = Queue()

# Submit tasks
for task in TASKS1:
task_queue.put(task)

# Start worker processes
for i in range(NUMBER_OF_PROCESSES):
Process(target=worker, args=(task_queue, done_queue)).start()

# Get and print results
print 'Unordered results:'
for i in range(len(TASKS1)):
print '\t', done_queue.get()

# Add more tasks using `put()`
for task in TASKS2:
task_queue.put(task)

# Get and print some more results
for i in range(len(TASKS2)):
print '\t', done_queue.get()

# Tell child processes to stop
for i in range(NUMBER_OF_PROCESSES):
task_queue.put('STOP')

test()

最佳答案

尝试用实际需要 CPU 的东西替换 time.sleep,您会看到 multiprocess 工作得很好!例如:

def mul(a, b):
for i in xrange(100000):
j = i**2
return a * b

def plus(a, b):
for i in xrange(100000):
j = i**2
return a + b

关于Python 多处理只使用一个内核,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/6905264/

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