metacomputing

简明释义

英[ˌmɛtəʊkəmˈpjuːtɪŋ]美[ˌmɛtəˈkɑmpjuːtɪŋ]

元计算

英英释义

单词用法

同义词

反义词

例句

1.PVM and MPI , which are popular parallel programming environments, will be integrated into the metacomputing system as the infrastructure of parallel computing.

PVM和MPI是广泛使用的并行编程环境，它们需要作为并行计算的基本构建而集成到元计算系统中去。

2.This paper analyzes and compares the existing fashions of high performance computing, and explains the relation between Grid and Metacomputing.

对高性能计算的各种方式进行了分析和比较，并阐述了网格和元计算的关系。

3.PVM and MPI , which are popular parallel programming environments, will be integrated into the metacomputing system as the infrastructure of parallel computing.

PVM和MPI是广泛使用的并行编程环境，它们需要作为并行计算的基本构建而集成到元计算系统中去。

4.The rise of cloud computing has made metacomputing 元计算 more accessible to businesses looking to optimize their computational tasks.

云计算的兴起使得寻求优化计算任务的企业更容易接触到 metacomputing 元计算。

5.Researchers are exploring metacomputing 元计算 techniques to improve the efficiency of resource allocation in grid computing environments.

研究人员正在探索 metacomputing 元计算 技术，以提高网格计算环境中资源分配的效率。

6.Using metacomputing 元计算, scientists can simulate weather patterns more accurately by utilizing resources from various supercomputers.

通过使用 metacomputing 元计算，科学家可以通过利用各种超级计算机的资源，更准确地模拟天气模式。

7.In the field of distributed systems, metacomputing 元计算 allows researchers to harness the power of multiple computers to solve complex problems.

在分布式系统领域，metacomputing 元计算 使研究人员能够利用多台计算机的力量来解决复杂问题。

8.The concept of metacomputing 元计算 is crucial for developing efficient algorithms for large-scale data processing.

对于大规模数据处理的高效算法开发，metacomputing 元计算 概念至关重要。

作文

In the rapidly evolving world of technology, the term metacomputing (元计算) has emerged as a significant concept that encapsulates the advanced methodologies and frameworks for managing computational resources. Essentially, metacomputing refers to the use of computing systems to optimize and control other computing systems. This layered approach allows for a more efficient allocation of resources and enhances the overall performance of computational tasks. The foundation of metacomputing lies in its ability to abstract the complexities of various computing environments. By providing a higher-level interface, it enables users to interact with multiple systems seamlessly, without needing to understand the intricate details of each individual system. This is particularly useful in environments where diverse computing resources are available, such as clusters, grids, and cloud computing platforms.One of the most significant advantages of metacomputing is its capability to facilitate resource sharing among different users and applications. In traditional computing environments, resources are often underutilized due to rigid allocation methods. However, metacomputing allows for dynamic resource management, where computing power can be distributed according to current demands. This not only maximizes efficiency but also reduces operational costs.Moreover, metacomputing plays a crucial role in scientific research and simulations. Researchers often require vast amounts of computational power for complex simulations, and metacomputing provides the necessary tools to harness this power effectively. For instance, in fields such as climate modeling, molecular dynamics, and astrophysics, researchers can utilize metacomputing to run extensive simulations across multiple systems simultaneously. This capability accelerates the pace of discovery and innovation.Another important aspect of metacomputing is its contribution to the development of new algorithms and applications. As more sophisticated computing systems are designed, the need for advanced algorithms that can leverage these systems becomes paramount. Metacomputing provides a framework for developing such algorithms, enabling researchers and developers to create applications that can dynamically adapt to the available resources and optimize their performance accordingly.Furthermore, the integration of metacomputing with emerging technologies, such as artificial intelligence and machine learning, opens up new avenues for innovation. These technologies can benefit from the resource management capabilities of metacomputing, allowing AI systems to access and process large datasets more efficiently. This synergy can lead to breakthroughs in various fields, including healthcare, finance, and engineering, where data-driven decision-making is crucial.In conclusion, metacomputing represents a transformative approach to computing that enhances resource management, fosters collaboration, and accelerates scientific research. As technology continues to advance, the importance of metacomputing will only grow, paving the way for more efficient and innovative computing solutions. By embracing metacomputing, we can unlock the full potential of our computational resources and drive progress across numerous domains, ultimately leading to a more connected and capable technological landscape.

在快速发展的技术世界中，术语metacomputing（元计算）作为一个重要概念出现，它概括了管理计算资源的先进方法和框架。基本上，metacomputing指的是使用计算系统来优化和控制其他计算系统。这种分层方法允许更有效地分配资源，并增强计算任务的整体性能。metacomputing的基础在于其抽象各种计算环境复杂性的能力。通过提供更高层次的接口，它使用户能够无缝地与多个系统进行交互，而无需了解每个单独系统的复杂细节。这在可用多种计算资源的环境中尤其有用，例如集群、网格和云计算平台。metacomputing的一个显著优势是其促进不同用户和应用程序之间资源共享的能力。在传统的计算环境中，由于严格的分配方法，资源往往未得到充分利用。然而，metacomputing允许动态资源管理，在这种管理中，计算能力可以根据当前需求进行分配。这不仅最大化了效率，还降低了运营成本。此外，metacomputing在科学研究和模拟中发挥着至关重要的作用。研究人员通常需要大量的计算能力来进行复杂的模拟，而metacomputing提供了有效利用这种能力的必要工具。例如，在气候建模、分子动力学和天体物理等领域，研究人员可以利用metacomputing在多个系统上同时运行广泛的模拟。这种能力加速了发现和创新的步伐。metacomputing的另一个重要方面是它对新算法和应用程序开发的贡献。随着越来越复杂的计算系统的设计，对能够利用这些系统的先进算法的需求变得至关重要。metacomputing提供了开发此类算法的框架，使研究人员和开发人员能够创建能够动态适应可用资源并相应优化其性能的应用程序。此外，metacomputing与人工智能和机器学习等新兴技术的集成开辟了创新的新途径。这些技术可以从metacomputing的资源管理能力中受益，使AI系统能够更高效地访问和处理大型数据集。这种协同作用可以在医疗保健、金融和工程等各个领域带来突破，这些领域中的数据驱动决策至关重要。总之，metacomputing代表了一种变革性的方法，它增强了资源管理，促进了合作，加速了科学研究。随着技术的不断进步，metacomputing的重要性只会增加，为更高效和创新的计算解决方案铺平道路。通过接受metacomputing，我们可以释放计算资源的全部潜力，并推动各个领域的进步，最终导致一个更加互联和强大的技术格局。