distributed computing

简明释义

分布式计算

英英释义

例句

1.The rise of big data analytics has fueled the growth of distributed computing 分布式计算 frameworks.

大数据分析的兴起推动了分布式计算 分布式计算 框架的增长。

2.Many modern applications rely on distributed computing 分布式计算 to handle large volumes of data efficiently.

许多现代应用依赖于分布式计算 分布式计算 来高效处理大量数据。

3.Cloud services utilize distributed computing 分布式计算 to provide scalable resources to users.

云服务利用分布式计算 分布式计算 为用户提供可扩展的资源。

4.With distributed computing 分布式计算, tasks can be processed in parallel across multiple machines.

通过分布式计算 分布式计算，任务可以在多台机器上并行处理。

5.The research team implemented distributed computing 分布式计算 to analyze complex simulations faster.

研究团队实施了分布式计算 分布式计算 以更快地分析复杂的模拟。

作文

In today's digital age, the demand for processing power and data management has grown exponentially. One of the most effective solutions to this challenge is distributed computing. This approach involves breaking down complex computational tasks into smaller, manageable parts that can be processed simultaneously across multiple machines or nodes. The concept of distributed computing allows for enhanced efficiency, scalability, and reliability in various applications, ranging from scientific research to cloud services.To understand distributed computing, it is essential to recognize its fundamental components. Typically, a distributed computing system consists of several interconnected computers, often referred to as nodes, which work together to achieve a common goal. Each node operates independently but collaborates with others to share resources and information. This collaboration minimizes the workload on a single machine and significantly speeds up the processing time.One of the key advantages of distributed computing is its ability to handle large volumes of data efficiently. In traditional computing models, a single server may struggle to process vast datasets due to limitations in memory and processing power. However, by distributing the workload across multiple nodes, distributed computing enables organizations to leverage the combined power of many computers, resulting in faster data processing and analysis.Moreover, distributed computing enhances system reliability. In a centralized system, if the main server fails, the entire operation comes to a halt. Conversely, in a distributed computing environment, if one node goes down, the remaining nodes can continue functioning, ensuring that the system remains operational. This fault tolerance is crucial for critical applications, such as financial transactions and healthcare data management, where downtime can have severe consequences.The scalability of distributed computing is another significant benefit. As the demand for processing power increases, organizations can easily add more nodes to their network, allowing them to scale their operations without overhauling their entire infrastructure. This flexibility is particularly valuable for businesses that experience fluctuating workloads, as it enables them to adapt to changing demands quickly.Applications of distributed computing are vast and varied. For example, in the field of scientific research, researchers can utilize distributed computing to analyze large datasets generated from experiments, simulations, or observational studies. Projects like SETI@home have demonstrated how millions of volunteers can contribute their computer's idle processing power to analyze radio signals from space, showcasing the power of distributed computing in solving complex problems.In addition to scientific applications, distributed computing plays a critical role in cloud computing services. Major cloud service providers, such as Amazon Web Services and Microsoft Azure, rely on distributed computing architectures to deliver scalable and reliable services to millions of users worldwide. By distributing resources across multiple data centers, these providers can ensure high availability and performance for their customers.In conclusion, distributed computing is a powerful paradigm that addresses the challenges of modern computing by distributing tasks across multiple nodes. Its benefits include enhanced efficiency, reliability, and scalability, making it an indispensable tool in various fields, from scientific research to cloud services. As technology continues to evolve, the importance and application of distributed computing will only grow, paving the way for innovative solutions to complex problems in our increasingly interconnected world.

在今天的数字时代，对处理能力和数据管理的需求呈指数增长。解决这一挑战的最有效方法之一是分布式计算。这种方法涉及将复杂的计算任务分解为更小、更易于管理的部分，这些部分可以在多个机器或节点上同时处理。分布式计算的概念使得在各个应用中实现更高的效率、可扩展性和可靠性成为可能，从科学研究到云服务。要理解分布式计算，首先要认识其基本组成部分。通常，分布式计算系统由多个互连的计算机组成，通常称为节点，这些节点共同工作以实现共同目标。每个节点独立运行，但与其他节点协作共享资源和信息。这种协作最小化了单台机器的工作负载，并显著加快了处理时间。分布式计算的一个关键优势是其高效处理大量数据的能力。在传统计算模型中，单个服务器可能因内存和处理能力的限制而难以处理庞大的数据集。然而，通过将工作负载分配到多个节点，分布式计算使组织能够利用多台计算机的综合能力，从而实现更快的数据处理和分析。此外，分布式计算增强了系统的可靠性。在集中式系统中，如果主服务器出现故障，整个操作将停止。相反，在分布式计算环境中，如果一个节点宕机，其余节点仍然可以继续运行，确保系统保持操作。这种容错能力对于关键应用至关重要，例如金融交易和医疗数据管理，因为停机可能会产生严重后果。分布式计算的可扩展性是另一个显著的好处。随着对处理能力的需求增加，组织可以轻松地向其网络添加更多节点，使他们能够在不全面改造整个基础设施的情况下扩展运营。这种灵活性对于经历波动工作负载的企业尤其有价值，因为它使他们能够快速适应变化的需求。分布式计算的应用广泛而多样。例如，在科学研究领域，研究人员可以利用分布式计算来分析实验、模拟或观察研究生成的大型数据集。像SETI@home这样的项目展示了数百万志愿者如何贡献他们计算机的闲置处理能力来分析来自太空的无线电信号，展示了分布式计算在解决复杂问题中的强大能力。除了科学应用，分布式计算在云计算服务中也发挥着关键作用。主要的云服务提供商，如亚马逊网络服务和微软Azure，依赖于分布式计算架构为全球数百万用户提供可扩展和可靠的服务。通过在多个数据中心分配资源，这些提供商能够确保对其客户的高可用性和性能。总之，分布式计算是一种强大的范例，通过在多个节点之间分配任务来解决现代计算中的挑战。其优点包括提高效率、可靠性和可扩展性，使其成为各个领域不可或缺的工具，从科学研究到云服务。随着技术的不断发展，分布式计算的重要性和应用只会增加，为我们日益互联的世界中的复杂问题提供创新解决方案。