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Copy file name to clipboardExpand all lines: spec/design_topics/parallelism.rst
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# Parallelism
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Parallelism
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===========
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Parallelism is mostly, but not completely, an execution or runtime concern
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rather than an API concern. Execution semantics are out of scope for this API
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they offer, such as:
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- Via environment variables. This is the method of choice for BLAS libraries and libraries using OpenMP.
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- Via a keyword to individual functions or methods. Examples include the `n_jobs` keyword used in scikit-learn and the `workers` keyword used in SciPy.
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- Via a keyword to individual functions or methods. Examples include the ``n_jobs`` keyword used in scikit-learn and the ``workers`` keyword used in SciPy.
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- Build-time settings to enable a parallel or distributed backend.
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- Via letting the user set chunk sizes. Dask uses this approach.
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2. A common library providing a parallelization layer
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Option (1) may possibly fit in a future version of this array API standard.
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