.. _block-module:

Block-Wide "Collective" Primitives
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   :glob:
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   api/block

CUB block-level algorithms are specialized for execution by threads in the same CUDA thread block:

* :cpp:class:`cub::BlockAdjacentDifference` computes the difference between adjacent items partitioned across a CUDA thread block
* :cpp:class:`cub::BlockDiscontinuity` flags discontinuities within an ordered set of items partitioned across a CUDA thread block
* :cpp:struct:`cub::BlockExchange` rearranges data partitioned across a CUDA thread block
* :cpp:class:`cub::BlockHistogram` constructs block-wide histograms from data samples partitioned across a CUDA thread block
* :cpp:class:`cub::BlockLoad` loads a linear segment of items from memory into a CUDA thread block
* :cpp:class:`cub::BlockMergeSort` sorts items partitioned across a CUDA thread block
* :cpp:class:`cub::BlockRadixSort` sorts items partitioned across a CUDA thread block using radix sorting method
* :cpp:struct:`cub::BlockReduce` computes reduction of items partitioned across a CUDA thread block
* :cpp:class:`cub::BlockRunLengthDecode` decodes a run-length encoded sequence partitioned across a CUDA thread block
* :cpp:struct:`cub::BlockScan` computes a prefix scan of items partitioned across a CUDA thread block
* :cpp:struct:`cub::BlockShuffle` shifts items partitioned across a CUDA thread block
* :cpp:class:`cub::BlockStore` stores items partitioned across a CUDA thread block to a linear segment of memory