久久久久久久av_日韩在线中文_看一级毛片视频_日本精品二区_成人深夜福利视频_武道仙尊动漫在线观看

  1. <tfoot id='nU0Um'></tfoot>
      <bdo id='nU0Um'></bdo><ul id='nU0Um'></ul>

      <legend id='nU0Um'><style id='nU0Um'><dir id='nU0Um'><q id='nU0Um'></q></dir></style></legend>

      <small id='nU0Um'></small><noframes id='nU0Um'>

    1. <i id='nU0Um'><tr id='nU0Um'><dt id='nU0Um'><q id='nU0Um'><span id='nU0Um'><b id='nU0Um'><form id='nU0Um'><ins id='nU0Um'></ins><ul id='nU0Um'></ul><sub id='nU0Um'></sub></form><legend id='nU0Um'></legend><bdo id='nU0Um'><pre id='nU0Um'><center id='nU0Um'></center></pre></bdo></b><th id='nU0Um'></th></span></q></dt></tr></i><div class="qwawimqqmiuu" id='nU0Um'><tfoot id='nU0Um'></tfoot><dl id='nU0Um'><fieldset id='nU0Um'></fieldset></dl></div>

      Python 多處理只使用一個(gè)核心

      Python multiprocessing utilizes only one core(Python 多處理只使用一個(gè)核心)

      1. <legend id='du3WJ'><style id='du3WJ'><dir id='du3WJ'><q id='du3WJ'></q></dir></style></legend>
      2. <i id='du3WJ'><tr id='du3WJ'><dt id='du3WJ'><q id='du3WJ'><span id='du3WJ'><b id='du3WJ'><form id='du3WJ'><ins id='du3WJ'></ins><ul id='du3WJ'></ul><sub id='du3WJ'></sub></form><legend id='du3WJ'></legend><bdo id='du3WJ'><pre id='du3WJ'><center id='du3WJ'></center></pre></bdo></b><th id='du3WJ'></th></span></q></dt></tr></i><div class="qwawimqqmiuu" id='du3WJ'><tfoot id='du3WJ'></tfoot><dl id='du3WJ'><fieldset id='du3WJ'></fieldset></dl></div>

        <small id='du3WJ'></small><noframes id='du3WJ'>

          <bdo id='du3WJ'></bdo><ul id='du3WJ'></ul>
          <tfoot id='du3WJ'></tfoot>

            <tbody id='du3WJ'></tbody>

              • 本文介紹了Python 多處理只使用一個(gè)核心的處理方法,對(duì)大家解決問(wèn)題具有一定的參考價(jià)值,需要的朋友們下面隨著小編來(lái)一起學(xué)習(xí)吧!

                問(wèn)題描述

                限時(shí)送ChatGPT賬號(hào)..

                我正在嘗試使用 標(biāo)準(zhǔn) python 文檔中的代碼片段來(lái)學(xué)習(xí)如何使用多處理模塊.代碼粘貼在此消息的末尾.我在四核機(jī)器上的 Ubuntu 11.04 上使用 Python 2.7.1(根據(jù)系統(tǒng)監(jiān)視器,由于超線程,它給了我八個(gè)內(nèi)核)

                I'm trying out a code snippet from the standard python documentation to learn how to use the multiprocessing module. The code is pasted at the end of this message. I'm using Python 2.7.1 on Ubuntu 11.04 on a quad core machine (which according to the system monitor gives me eight cores due to hyper threading)

                問(wèn)題:盡管啟動(dòng)了多個(gè)進(jìn)程,但所有工作負(fù)載似乎都安排在一個(gè)內(nèi)核上,利用率接近 100%.有時(shí),所有工作負(fù)載都會(huì)遷移到另一個(gè)核心,但工作負(fù)載從未在它們之間分配.

                Problem: All workload seems to be scheduled to just one core, which gets close to 100% utilization, despite the fact that several processes are started. Occasionally all workload migrates to another core but the workload is never distributed among them.

                任何想法為什么會(huì)這樣?

                Any ideas why this is so?

                最好的問(wèn)候,

                保羅

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

                推薦答案

                嘗試將 time.sleep 替換為實(shí)際需要 CPU 的東西,您將看到 multiprocess 有效正好!例如:

                Try replacing the time.sleep with something that actually requires CPUs and you will see the multiprocess works just fine! For example:

                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
                

                這篇關(guān)于Python 多處理只使用一個(gè)核心的文章就介紹到這了,希望我們推薦的答案對(duì)大家有所幫助,也希望大家多多支持html5模板網(wǎng)!

                【網(wǎng)站聲明】本站部分內(nèi)容來(lái)源于互聯(lián)網(wǎng),旨在幫助大家更快的解決問(wèn)題,如果有圖片或者內(nèi)容侵犯了您的權(quán)益,請(qǐng)聯(lián)系我們刪除處理,感謝您的支持!

                相關(guān)文檔推薦

                What exactly is Python multiprocessing Module#39;s .join() Method Doing?(Python 多處理模塊的 .join() 方法到底在做什么?)
                Passing multiple parameters to pool.map() function in Python(在 Python 中將多個(gè)參數(shù)傳遞給 pool.map() 函數(shù))
                multiprocessing.pool.MaybeEncodingError: #39;TypeError(quot;cannot serialize #39;_io.BufferedReader#39; objectquot;,)#39;(multiprocessing.pool.MaybeEncodingError: TypeError(cannot serialize _io.BufferedReader object,)) - IT屋-程序員軟件開(kāi)
                Python Multiprocess Pool. How to exit the script when one of the worker process determines no more work needs to be done?(Python 多進(jìn)程池.當(dāng)其中一個(gè)工作進(jìn)程確定不再需要完成工作時(shí),如何退出腳本?) - IT屋-程序員
                How do you pass a Queue reference to a function managed by pool.map_async()?(如何將隊(duì)列引用傳遞給 pool.map_async() 管理的函數(shù)?)
                yet another confusion with multiprocessing error, #39;module#39; object has no attribute #39;f#39;(與多處理錯(cuò)誤的另一個(gè)混淆,“模塊對(duì)象沒(méi)有屬性“f)

                  <small id='UWWiq'></small><noframes id='UWWiq'>

                  <tfoot id='UWWiq'></tfoot>

                    • <bdo id='UWWiq'></bdo><ul id='UWWiq'></ul>
                      1. <i id='UWWiq'><tr id='UWWiq'><dt id='UWWiq'><q id='UWWiq'><span id='UWWiq'><b id='UWWiq'><form id='UWWiq'><ins id='UWWiq'></ins><ul id='UWWiq'></ul><sub id='UWWiq'></sub></form><legend id='UWWiq'></legend><bdo id='UWWiq'><pre id='UWWiq'><center id='UWWiq'></center></pre></bdo></b><th id='UWWiq'></th></span></q></dt></tr></i><div class="qwawimqqmiuu" id='UWWiq'><tfoot id='UWWiq'></tfoot><dl id='UWWiq'><fieldset id='UWWiq'></fieldset></dl></div>
                        <legend id='UWWiq'><style id='UWWiq'><dir id='UWWiq'><q id='UWWiq'></q></dir></style></legend>

                            <tbody id='UWWiq'></tbody>
                        1. 主站蜘蛛池模板: 免费色视频 | 国产三级精品三级在线观看 | a在线免费观看 | 日韩精品视频在线免费观看 | 视频一区二区在线播放 | 欧美日韩一二三区 | 日韩福利 | 国产人成一区二区三区影院 | 国产高潮在线观看 | 中文字幕在线看片 | 色影视| 涩涩视频免费观看 | 在线a| 日韩免费在线观看视频 | 精品视频在线免费观看 | av网站免费在线观看 | 国内自拍xxxx18| 成人一级毛片 | 欧美成人精品欧美一级私黄 | 亚洲色网址 | 久久天天躁狠狠躁夜夜躁2014 | 国产午夜视频 | 成人精品免费 | 欧美成人极品 | 亚洲欧美日韩精品 | 国产精品一线 | 欧美一级片网站 | 日韩 欧美 | 青草福利视频 | 国产精品福利视频 | 91少妇丨porny丨 | 一本到av| 一道本在线视频 | 日本a网站| 日韩成人免费 | 日韩 欧美 亚洲 | 青青久久久 | 日韩精品一级 | 亚洲欧美天堂 | 日韩免费看片 | av不卡在线观看 |