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150 :467

	English `boost::concurrent_flat_map<int, int>` 38/10000 · 38
151 :468

	English `boost::concurrent_node_map<int, int>` 38/10000 · 38
152 :470

	English The source code can be https://github.com/boostorg/boost_unordered_benchmarks/tree/boost_concurrent_flat_map[found here^]. 122/10000 · 122
153 :472

	English The benchmarks exercise a number of threads _T_ (between 1 and 16) concurrently performing operations randomly chosen among update, successful lookup and unsuccessful lookup. The keys used in the operations follow a https://en.wikipedia.org/wiki/Zipf%27s_law#Formal_definition[Zipf distribution^] with different _skew_ parameters: the higher the skew, the more concentrated are the keys in the lower values of the covered range. 440/10000 · 440
154 :478

	English `boost::concurrent_flat_map` and `boost::concurrent_node_map` are exercised using both regular and xref:concurrent.adoc#concurrent_bulk_visitation[bulk visitation]: in the latter case, lookup keys are buffered in a local array and then processed at once each time the buffer reaches `xref:reference/concurrent_flat_map.adoc#concurrent_flat_map_constants[bulk_visit_size]`. 372/10000 · 372
:482 :482

	English GCC 12, x64 11/10000 · 11
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	English image::benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.500k, 0.01.png"] 190/10000 · 190
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	English image::benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.500k, 0.5.png"] 188/10000 · 188
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	English image::benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.500k, 0.99.png"] 190/10000 · 190
:493 :493

	English h\|500k updates, 4.5M lookups + skew=0.01 h\|500k updates, 4.5M lookups + skew=0.5 h\|500k updates, 4.5M lookups + skew=0.99 \|=== 126/10000 · 126
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	English image::benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.5M, 0.01.png"] 186/10000 · 186
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	English image::benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.5M, 0.5.png"] 184/10000 · 184
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	English image::benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/gcc-x64/Parallel workload.xlsx.5M, 0.99.png"] 186/10000 · 186
:509 :509

	English h\|5M updates, 45M lookups + skew=0.01 h\|5M updates, 45M lookups + skew=0.5 h\|5M updates, 45M lookups + skew=0.99 \|=== 117/10000 · 117
:517 :517

	English Clang 15, x64 13/10000 · 13
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	English image::benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.500k, 0.01.png"] 194/10000 · 194
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	English image::benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.500k, 0.5.png"] 192/10000 · 192
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	English image::benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.500k, 0.99.png"] 194/10000 · 194
:528 :528

	English h\|500k updates, 4.5M lookups + skew=0.01 h\|500k updates, 4.5M lookups + skew=0.5 h\|500k updates, 4.5M lookups + skew=0.99 \|=== 126/10000 · 126
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	English image::benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.01.png"] 190/10000 · 190

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