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Distributed computing refers to a model of computation where tasks are divided among multiple computers, which communicate and coordinate their actions by passing messages. This approach contrasts with centralized computing, where a single computer or server handles all tasks. Distributed computing is often used to improve reliability, performance, and resource sharing.

One of the key advantages of distributed computing is fault tolerance. Since tasks are spread across multiple computers, the failure of one computer does not necessarily bring down the entire system. This redundancy can enhance the reliability of applications and services.

Another benefit is scalability. Distributed systems can easily scale by adding more computers to the network. This makes it possible to handle large volumes of data and high levels of traffic without significant performance degradation.

Distributed computing is employed in various fields, including scientific research, where complex simulations and data analysis can be parallelized across multiple machines. It is also used in web services and cloud computing, where resources are dynamically allocated and managed across a network of servers.

However, distributed computing also presents challenges. Ensuring data consistency and synchronization across multiple nodes can be complex. Network latency and communication overhead can impact performance. Additionally, managing and coordinating the actions of multiple computers requires sophisticated algorithms and protocols.

In summary, distributed computing is a powerful paradigm that leverages multiple computers to achieve greater reliability, performance, and scalability. While it offers numerous benefits, it also introduces complexities that need to be carefully managed.