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Going parallel and larger-than-memory with graphs


Dask is an open source, pure python library that enables parallel larger-than-memory computation in a novel way. We represent programs as Directed Acyclic Graphs (DAG) of function calls. These graphs are executed by dask's schedulers with different optimizations (synchronous, threaded, parallel, distributed-memory). Dask has modules geared towards data analysis, which provide a friendly interface to building graps. One module, dask.array, mimics a subset of NumPy operations. With dask.array we can work with NumPy like arrays that are larger than RAM and parallelization comes for free by leveraging the underlying DAG.


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