Parallelism

Parallelism refers to the ability to perform multiple tasks or computations simultaneously. In the context of data science and artificial intelligence, parallelism is used to speed up the processing of large datasets and complex algorithms. Parallelism can be achieved through various techniques such as multi-threading, multi-processing, and distributed computing. Multi-threading involves dividing a single task into smaller sub-tasks that can be executed concurrently by different threads within a single processor. Multi-processing involves distributing the workload across multiple processors or cores within a single machine. Distributed computing involves distributing the workload across multiple machines connected through a network. Parallelism is essential for achieving high performance and scalability in data science and artificial intelligence applications.
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