Dask and multiprocessing are both tools for parallel computing, but they have differences in performance and scalability. Dask is better suited for tasks that involve large datasets and complex computations, as it can handle distributed computing across multiple machines. On the other hand, multiprocessing is more efficient for tasks that require simple parallel processing on a single machine. In terms of scalability, Dask can scale to larger datasets and more complex computations, while multiprocessing may struggle with scaling beyond a certain point due to limitations in memory and processing power.
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