Distributed Computing Systems
Distributed Computing Systems refer to a network of computers that work together to solve a complex problem or perform a large-scale computation. In this system, each computer node has its own memory and processing power, and they communicate with each other through message passing. The goal of distributed computing is to achieve high performance, reliability, and fault tolerance. Distributed computing systems are widely used in data science and artificial intelligence applications, such as distributed machine learning, distributed data processing, and distributed deep learning. These systems enable data scientists and AI experts to process large datasets and train complex models in a distributed and parallel manner, which can significantly reduce the computation time and improve the scalability of the system.
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