mirror of
https://github.com/NVIDIA/cuda-samples.git
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67 lines
2.1 KiB
XML
67 lines
2.1 KiB
XML
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<?xml version="1.0" encoding="UTF-8"?>
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<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
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<entry>
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<name>sortingNetworks</name>
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<description><![CDATA[This sample implements bitonic sort and odd-even merge sort (also known as Batcher's sort), algorithms belonging to the class of sorting networks. While generally subefficient, for large sequences compared to algorithms with better asymptotic algorithmic complexity (i.e. merge sort or radix sort), this may be the preferred algorithms of choice for sorting batches of short-sized to mid-sized (key, value) array pairs. Refer to an excellent tutorial by H. W. Lang http://www.iti.fh-flensburg.de/lang/algorithmen/sortieren/networks/indexen.htm]]></description>
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<devicecompilation>whole</devicecompilation>
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<includepaths>
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<path>./</path>
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<path>../</path>
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<path>../../Common</path>
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</includepaths>
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<keyconcepts>
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<concept level="advanced">Data-Parallel Algorithms</concept>
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</keyconcepts>
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<keywords>
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<keyword>sort</keyword>
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<keyword>bitonic</keyword>
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<keyword>CUDA</keyword>
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</keywords>
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<libraries>
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</libraries>
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<librarypaths>
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</librarypaths>
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<nsight_eclipse>true</nsight_eclipse>
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<primary_file>main.cpp</primary_file>
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<scopes>
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<scope>1:CUDA Basic Topics</scope>
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<scope>1:Data-Parallel Algorithms</scope>
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</scopes>
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<sm-arch>sm35</sm-arch>
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<sm-arch>sm37</sm-arch>
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<sm-arch>sm50</sm-arch>
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<sm-arch>sm52</sm-arch>
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<sm-arch>sm60</sm-arch>
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<sm-arch>sm61</sm-arch>
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<sm-arch>sm70</sm-arch>
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<sm-arch>sm72</sm-arch>
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<sm-arch>sm75</sm-arch>
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<sm-arch>sm80</sm-arch>
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<sm-arch>sm86</sm-arch>
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<supported_envs>
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<env>
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<arch>x86_64</arch>
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<platform>linux</platform>
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</env>
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<env>
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<platform>windows7</platform>
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</env>
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<env>
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<arch>x86_64</arch>
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<platform>macosx</platform>
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</env>
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<env>
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<arch>arm</arch>
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</env>
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<env>
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<arch>ppc64le</arch>
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<platform>linux</platform>
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</env>
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</supported_envs>
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<supported_sm_architectures>
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<include>all</include>
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</supported_sm_architectures>
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<title>CUDA Sorting Networks</title>
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<type>exe</type>
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</entry>
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