parallel machine

简明释义

并行计算机

英英释义

例句

1.Engineers tested the new parallel machine 并行机器 to ensure it met the required specifications.

工程师测试了新的parallel machine 并行机器，以确保其符合所需规格。

2.The software was designed to run on a parallel machine 并行机器 to take advantage of its computational power.

该软件被设计为在parallel machine 并行机器上运行，以利用其计算能力。

3.Using a parallel machine 并行机器 allows for faster simulations in scientific research.

使用parallel machine 并行机器可以加快科学研究中的模拟速度。

4.In data processing, a parallel machine 并行机器 can handle multiple tasks simultaneously, improving efficiency.

在数据处理过程中，parallel machine 并行机器可以同时处理多个任务，提高效率。

5.The factory upgraded its production line to include a new parallel machine 并行机器 that significantly increased output.

工厂升级了生产线，引入了一台新的parallel machine 并行机器，显著提高了产量。

作文

In the modern era of technology, the efficiency of computing systems plays a vital role in various industries. One of the significant advancements in this field is the development of the parallel machine (并行机器). A parallel machine refers to a computing system that can perform multiple operations simultaneously. This capability is essential for handling large datasets and complex computations, which are increasingly common in today's data-driven world. The concept of parallelism has been around for decades, but with the advent of multi-core processors and distributed computing, the implementation of parallel machines has become more practical and widespread. These machines can be found in supercomputers, cloud computing platforms, and even in personal computers equipped with multi-core CPUs. By utilizing multiple cores or processors, a parallel machine can divide tasks into smaller sub-tasks and process them concurrently, significantly reducing the overall computation time.One of the primary advantages of parallel machines is their ability to handle intensive computational tasks efficiently. For instance, in scientific research, simulations that require vast amounts of calculations can benefit immensely from the use of parallel machines. Researchers can run complex models in a fraction of the time it would take on a traditional, single-threaded machine. This acceleration not only saves time but also allows for more iterations and refinements in research, leading to better results.Moreover, the rise of big data has created a demand for systems capable of processing large volumes of information quickly. Parallel machines excel in this area by enabling data to be processed in chunks rather than sequentially. In fields like finance, healthcare, and social media analytics, organizations rely on parallel machines to analyze trends, predict outcomes, and make data-driven decisions in real-time.However, working with parallel machines does come with its challenges. Programming for parallel execution requires a different approach compared to traditional sequential programming. Developers must consider issues such as data synchronization, load balancing, and potential bottlenecks that can arise when multiple processes attempt to access shared resources. Tools and frameworks have been developed to assist programmers in writing efficient parallel code, but it still requires a solid understanding of the underlying principles of parallel computing.In conclusion, the emergence of parallel machines has transformed the landscape of computing by providing enhanced performance and efficiency. As technology continues to evolve, the importance of these machines will only grow, making them indispensable in various sectors. Understanding how to leverage the power of parallel machines will be crucial for future innovations in computing and data analysis, ultimately shaping the way we interact with technology and process information in our daily lives.

在现代科技时代，计算系统的效率在各个行业中扮演着至关重要的角色。这个领域的一个重大进展是并行机器（parallel machine）的发展。并行机器指的是能够同时执行多个操作的计算系统。这种能力对于处理大数据集和复杂计算至关重要，这在当今数据驱动的世界中愈发普遍。并行的概念已经存在了几十年，但随着多核处理器和分布式计算的出现，并行机器的实现变得更加实用和广泛。这些机器可以在超级计算机、云计算平台，甚至在配备多核CPU的个人电脑中找到。通过利用多个核心或处理器，并行机器能够将任务分解为更小的子任务并同时处理，从而显著减少整体计算时间。并行机器的主要优势之一是它们能够高效地处理密集的计算任务。例如，在科学研究中，需要大量计算的模拟可以从使用并行机器中获得巨大收益。研究人员可以在传统单线程机器所需时间的一小部分内运行复杂模型。这种加速不仅节省了时间，还允许在研究中进行更多的迭代和改进，从而导致更好的结果。此外，大数据的兴起对快速处理大量信息的系统提出了需求。并行机器在这一领域表现出色，它们能够以块的形式处理数据，而不是顺序处理。在金融、医疗保健和社交媒体分析等领域，组织依赖于并行机器来实时分析趋势、预测结果并做出数据驱动的决策。然而，使用并行机器也带来了挑战。与传统的顺序编程相比，为并行执行编程需要不同的方法。开发人员必须考虑数据同步、负载平衡以及当多个进程尝试访问共享资源时可能出现的瓶颈等问题。已经开发出工具和框架来帮助程序员编写高效的并行代码，但这仍然需要对并行计算的基本原理有扎实的理解。总之，并行机器的出现通过提供增强的性能和效率改变了计算的格局。随着技术的不断发展，这些机器的重要性只会增加，使其在各个领域中不可或缺。理解如何利用并行机器的强大功能对于未来计算和数据分析中的创新至关重要，最终将塑造我们与技术互动和处理信息的方式。