multiprocessing

简明释义

英[ˌmʌltiˈprəʊsesɪŋ]美[ˌmʌltiˈprɑːsesɪŋ]

n. 多重处理

英英释义

单词用法

同义词

反义词

例句

1.SMP, or symmetric multiprocessing.

即对称多处理(symmetricmultiprocessing)。

2.In a multiprocessing environment, the processing time for a thread is related to the availability of system resources and synchronization with other threads.

在多处理环境中，线程的处理时间与可用系统资源以及与其他线程的同步有关。

3.Thus, multiprocessing systems can be assembled on a single board.

因此，在一块板上能组装出多处理系统。

4.What is multiprocessing?

什么是多重处理？

5.I realize that there are a number of questions on multiprocessing, but so far I haven't been able to solve this issue.

我知道有一些问题在多处理器，但到目前为止我没能解决这个问题。

6.The multiprocessing system is one of the most important parts of infrared imaging and detecting systems.

引言多处理器系统作为红外成像探测系统的重要组成部分，主要完成红外图像处理和目标检测。

7.The application uses multiprocessing to speed up data processing tasks.

该应用程序使用多进程处理来加快数据处理任务。

8.By implementing multiprocessing, we can utilize multiple CPU cores efficiently.

通过实现多进程处理，我们可以有效利用多个CPU核心。

9.Python's multiprocessing module allows the creation of separate processes for tasks.

Python的多进程处理模块允许为任务创建独立的进程。

10.Using multiprocessing, the program can handle several tasks simultaneously.

使用多进程处理，程序可以同时处理多个任务。

11.The server employs multiprocessing to manage multiple client requests at once.

服务器采用多进程处理来同时管理多个客户端请求。

作文

In the world of computing, efficiency and speed are paramount. One of the most significant advancements in this field is the concept of multiprocessing, which refers to the ability of a system to utilize multiple processors or cores simultaneously to execute tasks. This capability allows for the parallel execution of processes, significantly enhancing performance and reducing the time required to complete complex computations. In this essay, I will explore the importance of multiprocessing in modern computing, its applications, and its impact on various industries. To begin with, multiprocessing is an essential feature in modern operating systems and software development. It enables programs to perform several operations at once, rather than sequentially. For example, in a typical application, one processor might be responsible for handling user input, while another processes data in the background. This division of labor not only speeds up the overall operation of the program but also improves the user experience by making applications more responsive. The applications of multiprocessing are vast and varied. In scientific computing, simulations that require extensive calculations can benefit immensely from this technology. Instead of waiting for one calculation to finish before starting the next, researchers can run multiple simulations at the same time, leading to faster results and more efficient use of resources. Similarly, in the realm of data analysis, multiprocessing allows analysts to process large datasets more quickly, enabling them to derive insights and make decisions in a timely manner. Moreover, multiprocessing plays a crucial role in the development of artificial intelligence (AI) and machine learning (ML). Training complex models often requires processing vast amounts of data and performing numerous calculations. By leveraging multiprocessing, developers can train models more efficiently, reducing the time it takes to achieve accurate results. This acceleration is vital in industries where timely data-driven decisions are critical, such as finance, healthcare, and autonomous driving. In addition to its technical advantages, multiprocessing also fosters innovation across various sectors. For instance, in the film industry, rendering high-quality visual effects can be incredibly time-consuming. However, with multiprocessing, studios can distribute rendering tasks across multiple processors, drastically cutting down production times. This capability allows filmmakers to experiment with more complex visuals and storytelling techniques, ultimately enhancing the quality of cinematic experiences. Furthermore, the rise of cloud computing has amplified the importance of multiprocessing. Cloud service providers offer scalable resources that can handle multiple processes concurrently, allowing businesses to adapt to varying workloads without investing in expensive hardware. This flexibility empowers organizations to innovate and grow without being hindered by their computing capabilities. In conclusion, multiprocessing is a transformative technology that has reshaped the landscape of computing. Its ability to execute multiple processes simultaneously enhances efficiency, accelerates research and development, and drives innovation across various industries. As we continue to advance technologically, the importance of multiprocessing will only grow, paving the way for even more sophisticated applications and solutions. Embracing this technology is essential for anyone looking to thrive in the fast-paced digital world of today.

在计算机的世界中，效率和速度至关重要。其中一个最显著的进展是multiprocessing的概念，它指的是系统同时利用多个处理器或核心来执行任务的能力。这种能力允许并行执行进程，显著提高性能并减少完成复杂计算所需的时间。在这篇文章中，我将探讨multiprocessing在现代计算中的重要性、应用及其对各个行业的影响。 首先，multiprocessing是现代操作系统和软件开发中的一个基本特征。它使程序能够同时执行多个操作，而不是顺序执行。例如，在一个典型的应用程序中，一个处理器可能负责处理用户输入，而另一个则在后台处理数据。这种分工不仅加快了程序的整体运行速度，还通过使应用程序更具响应性来改善用户体验。 multiprocessing的应用范围广泛且多样。在科学计算中，需要大量计算的模拟可以从这一技术中受益匪浅。研究人员可以同时运行多个模拟，而不必等待一个计算完成后再开始下一个，从而导致更快的结果和更高效的资源使用。类似地，在数据分析领域，multiprocessing使分析师能够更快地处理大型数据集，使他们能够及时得出见解并做出决策。 此外，multiprocessing在人工智能（AI）和机器学习（ML）的发展中也发挥着至关重要的作用。训练复杂模型通常需要处理大量数据并进行无数计算。通过利用multiprocessing，开发人员可以更高效地训练模型，减少获得准确结果所需的时间。这种加速在金融、医疗和自动驾驶等行业中至关重要，因为这些行业需要及时的数据驱动决策。 除了技术优势，multiprocessing还促进了各个行业的创新。例如，在电影行业，渲染高质量视觉效果可能非常耗时。然而，通过multiprocessing，制片厂可以将渲染任务分配到多个处理器上，从而大幅缩短制作时间。这种能力使电影制作人能够尝试更复杂的视觉效果和叙事技巧，最终提升电影体验的质量。 此外，云计算的兴起进一步增强了multiprocessing的重要性。云服务提供商提供可扩展的资源，可以同时处理多个进程，使企业能够在不投资昂贵硬件的情况下适应不同的工作负载。这种灵活性使组织能够创新和发展，而不会受到计算能力的限制。 总之，multiprocessing是一项变革性技术，重新塑造了计算领域的格局。它同时执行多个进程的能力提高了效率，加速了研发，并推动了各个行业的创新。随着我们在技术上的持续进步，multiprocessing的重要性只会增加，为更复杂的应用和解决方案铺平道路。拥抱这一技术对于任何希望在当今快速发展的数字世界中蓬勃发展的个人而言都是至关重要的。