👉 Cluster computing is a distributed computing paradigm where multiple computers, known as nodes, work together to solve large-scale computational problems. These nodes are interconnected through a network and share resources such as processing power, memory, and storage to achieve higher performance and efficiency than a single machine could provide. By dividing tasks among the nodes, cluster computing allows for parallel processing, significantly reducing computation time and enabling the handling of complex, data-intensive tasks that would otherwise be infeasible. This approach is widely used in scientific research, big data analytics, machine learning, and other fields requiring substantial computational resources.
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What is the definition of Cluster Computing? 🙋
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What is the definition of Clusters Computing? 🙋
👉 Cluster computing is a method of distributing computational tasks across multiple interconnected computers, or nodes, to achieve greater efficiency and scalability in processing large-scale problems. In this setup, each node can perform its own computations, and they communicate with one another to share data and coordinate tasks. This approach allows for the parallel execution of processes, significantly reducing the time required to solve complex problems that would be impractical or impossible for a single machine to handle. Clusters are commonly used in scientific research, big data analytics, machine learning, and high-performance computing applications where the volume of data or the complexity of computations demands more resources than a single computer can provide. By leveraging the combined power of multiple nodes, cluster computing enables organizations to tackle intricate challenges more effectively and efficiently.
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