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fix xrefs and image paths

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Christian Mazakas
2025-01-03 09:46:02 -08:00
parent 6f432c0d98
commit db31da1302
13 changed files with 205 additions and 212 deletions
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doc/modules/ROOT/pages/benchmarks.adoc
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@ -1,6 +1,5 @@
[#benchmarks]
:idprefix: benchmarks_
:imagesdir: ../diagrams
= Benchmarks
@ -24,9 +23,9 @@ The unsuccessful lookup benchmarks use `n` randomly generated integers but using
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/gcc/running insertion.xlsx.practice.png[width=250,link=../diagrams/benchmarks-set/gcc/running insertion.xlsx.practice.png,window=_blank]
|image::benchmarks-set/gcc/running%20insertion.xlsx.practice non-unique.png[width=250,link=../diagrams/benchmarks-set/gcc/running%20insertion.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/gcc/running%20insertion.xlsx.practice non-unique 5.png[width=250,link=../diagrams/benchmarks-set/gcc/running%20insertion.xlsx.practice non-unique 5.png,window=_blank]
|image::benchmarks-set/gcc/running insertion.xlsx.practice.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice.png,window=_blank]
|image::benchmarks-set/gcc/running insertion.xlsx.practice non-unique.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/gcc/running insertion.xlsx.practice non-unique 5.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice non-unique 5.png,window=_blank]
h|non-duplicate elements
h|duplicate elements
@ -38,9 +37,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/gcc/running%20insertion.xlsx.practice norehash.png[width=250,link=../diagrams/benchmarks-set/gcc/running%20insertion.xlsx.practice norehash.png,window=_blank]
|image::benchmarks-set/gcc/running%20insertion.xlsx.practice norehash non-unique.png[width=250,link=../diagrams/benchmarks-set/gcc/running%20insertion.xlsx.practice norehash non-unique.png,window=_blank]
|image::benchmarks-set/gcc/running%20insertion.xlsx.practice norehash non-unique 5.png[width=250,link=../diagrams/benchmarks-set/gcc/running%20insertion.xlsx.practice norehash non-unique 5.png,window=_blank]
|image::benchmarks-set/gcc/running insertion.xlsx.practice norehash.png[width=250,link= _images/benchmarks-set/gcc/running insertion.xlsx.practice norehash.png,window=_blank]
|image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png[width=250,link= _images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png,window=_blank]
|image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png[width=250,link= _images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png,window=_blank]
h|non-duplicate elements, +
prior `reserve`
@ -58,9 +57,9 @@ prior `reserve`
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/gcc/scattered%20erasure.xlsx.practice.png[width=250,link=../diagrams/benchmarks-set/gcc/scattered%20erasure.xlsx.practice.png,window=_blank]
|image::benchmarks-set/gcc/scattered%20erasure.xlsx.practice non-unique.png[width=250,link=../diagrams/benchmarks-set/gcc/scattered%20erasure.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/gcc/scattered%20erasure.xlsx.practice non-unique 5.png[width=250,link=../diagrams/benchmarks-set/gcc/scattered%20erasure.xlsx.practice non-unique 5.png,window=_blank]
|image::benchmarks-set/gcc/scattered erasure.xlsx.practice.png[width=250,link= _images/benchmarks-set/gcc/scattered erasure.xlsx.practice.png,window=_blank]
|image::benchmarks-set/gcc/scattered erasure.xlsx.practice non-unique.png[width=250,link= _images/benchmarks-set/gcc/scattered erasure.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/gcc/scattered erasure.xlsx.practice non-unique 5.png[width=250,link= _images/benchmarks-set/gcc/scattered erasure.xlsx.practice non-unique 5.png,window=_blank]
h|non-duplicate elements
h|duplicate elements
@ -68,8 +67,8 @@ h|duplicate elements, +
max load factor 5
|
|image::benchmarks-set/gcc/scattered%20erasure%20by%20key.xlsx.practice non-unique.png[width=250,link=../diagrams/benchmarks-set/gcc/scattered%20erasure%20by%20key.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/gcc/scattered%20erasure%20by%20key.xlsx.practice non-unique 5.png[width=250,link=../diagrams/benchmarks-set/gcc/scattered%20erasure%20by%20key.xlsx.practice non-unique 5.png,window=_blank]
|image::benchmarks-set/gcc/scattered erasure by key.xlsx.practice non-unique.png[width=250,link= _images/benchmarks-set/gcc/scattered erasure by key.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/gcc/scattered erasure by key.xlsx.practice non-unique 5.png[width=250,link= _images/benchmarks-set/gcc/scattered erasure by key.xlsx.practice non-unique 5.png,window=_blank]
|
h|by key, duplicate elements
@ -84,9 +83,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/gcc/scattered%20successful%20looukp.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/gcc/scattered%20successful%20looukp.xlsx.practice.png]
|image::benchmarks-set/gcc/scattered%20successful%20looukp.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/gcc/scattered%20successful%20looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/gcc/scattered%20successful%20looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/gcc/scattered%20successful%20looukp.xlsx.practice non-unique 5.png]
|image::benchmarks-set/gcc/scattered successful looukp.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/gcc/scattered successful looukp.xlsx.practice.png]
|image::benchmarks-set/gcc/scattered successful looukp.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/gcc/scattered successful looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/gcc/scattered successful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/gcc/scattered successful looukp.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -101,9 +100,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/gcc/scattered%20unsuccessful%20looukp.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/gcc/scattered%20unsuccessful%20looukp.xlsx.practice.png]
|image::benchmarks-set/gcc/scattered%20unsuccessful%20looukp.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/gcc/scattered%20unsuccessful%20looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/gcc/scattered%20unsuccessful%20looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/gcc/scattered%20unsuccessful%20looukp.xlsx.practice non-unique 5.png]
|image::benchmarks-set/gcc/scattered unsuccessful looukp.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/gcc/scattered unsuccessful looukp.xlsx.practice.png]
|image::benchmarks-set/gcc/scattered unsuccessful looukp.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/gcc/scattered unsuccessful looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/gcc/scattered unsuccessful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/gcc/scattered unsuccessful looukp.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -120,9 +119,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice.png[width=250, window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice.png]
|image::benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice non-unique.png[width=250, window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice non-unique.png]
|image::benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice non-unique 5.png[width=250, window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice non-unique 5.png]
|image::benchmarks-set/clang_libcpp/running insertion.xlsx.practice.png[width=250, window=_blank,link= _images/benchmarks-set/clang_libcpp/running insertion.xlsx.practice.png]
|image::benchmarks-set/clang_libcpp/running insertion.xlsx.practice non-unique.png[width=250, window=_blank,link= _images/benchmarks-set/clang_libcpp/running insertion.xlsx.practice non-unique.png]
|image::benchmarks-set/clang_libcpp/running insertion.xlsx.practice non-unique 5.png[width=250, window=_blank,link= _images/benchmarks-set/clang_libcpp/running insertion.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -135,9 +134,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice norehash.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice norehash.png]
|image::benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice norehash non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice norehash non-unique.png]
|image::benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice norehash non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/running%20insertion.xlsx.practice norehash non-unique 5.png]
|image::benchmarks-set/clang_libcpp/running insertion.xlsx.practice norehash.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/running insertion.xlsx.practice norehash.png]
|image::benchmarks-set/clang_libcpp/running insertion.xlsx.practice norehash non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/running insertion.xlsx.practice norehash non-unique.png]
|image::benchmarks-set/clang_libcpp/running insertion.xlsx.practice norehash non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/running insertion.xlsx.practice norehash non-unique 5.png]
h|non-duplicate elements, +
prior `reserve`
@ -155,9 +154,9 @@ prior `reserve`
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/clang_libcpp/scattered%20erasure.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20erasure.xlsx.practice.png]
|image::benchmarks-set/clang_libcpp/scattered%20erasure.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20erasure.xlsx.practice non-unique.png]
|image::benchmarks-set/clang_libcpp/scattered%20erasure.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20erasure.xlsx.practice non-unique 5.png]
|image::benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice.png]
|image::benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice non-unique.png]
|image::benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -165,8 +164,8 @@ h|duplicate elements, +
max load factor 5
|
|image::benchmarks-set/clang_libcpp/scattered%20erasure%20by%20key.xlsx.practice non-unique.png[width=250,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20erasure%20by%20key.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/clang_libcpp/scattered%20erasure%20by%20key.xlsx.practice non-unique 5.png[width=250,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20erasure%20by%20key.xlsx.practice non-unique 5.png,window=_blank]
|image::benchmarks-set/clang_libcpp/scattered erasure by key.xlsx.practice non-unique.png[width=250,link= _images/benchmarks-set/clang_libcpp/scattered erasure by key.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/clang_libcpp/scattered erasure by key.xlsx.practice non-unique 5.png[width=250,link= _images/benchmarks-set/clang_libcpp/scattered erasure by key.xlsx.practice non-unique 5.png,window=_blank]
|
h|by key, duplicate elements
@ -181,9 +180,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/clang_libcpp/scattered%20successful%20looukp.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20successful%20looukp.xlsx.practice.png]
|image::benchmarks-set/clang_libcpp/scattered%20successful%20looukp.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20successful%20looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/clang_libcpp/scattered%20successful%20looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20successful%20looukp.xlsx.practice non-unique 5.png]
|image::benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice.png]
|image::benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -198,9 +197,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/clang_libcpp/scattered%20unsuccessful%20looukp.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20unsuccessful%20looukp.xlsx.practice.png]
|image::benchmarks-set/clang_libcpp/scattered%20unsuccessful%20looukp.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20unsuccessful%20looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/clang_libcpp/scattered%20unsuccessful%20looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/clang_libcpp/scattered%20unsuccessful%20looukp.xlsx.practice non-unique 5.png]
|image::benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice.png]
|image::benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -217,9 +216,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/vs/running%20insertion.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/running%20insertion.xlsx.practice.png]
|image::benchmarks-set/vs/running%20insertion.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/running%20insertion.xlsx.practice non-unique.png]
|image::benchmarks-set/vs/running%20insertion.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/running%20insertion.xlsx.practice non-unique 5.png]
|image::benchmarks-set/vs/running insertion.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/vs/running insertion.xlsx.practice.png]
|image::benchmarks-set/vs/running insertion.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/vs/running insertion.xlsx.practice non-unique.png]
|image::benchmarks-set/vs/running insertion.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/vs/running insertion.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -232,9 +231,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/vs/running%20insertion.xlsx.practice norehash.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/running%20insertion.xlsx.practice norehash.png]
|image::benchmarks-set/vs/running%20insertion.xlsx.practice norehash non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/running%20insertion.xlsx.practice norehash non-unique.png]
|image::benchmarks-set/vs/running%20insertion.xlsx.practice norehash non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/running%20insertion.xlsx.practice norehash non-unique 5.png]
|image::benchmarks-set/vs/running insertion.xlsx.practice norehash.png[width=250,window=_blank,link= _images/benchmarks-set/vs/running insertion.xlsx.practice norehash.png]
|image::benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique.png]
|image::benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique 5.png]
h|non-duplicate elements, +
prior `reserve`
@ -252,9 +251,9 @@ prior `reserve`
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/vs/scattered%20erasure.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20erasure.xlsx.practice.png]
|image::benchmarks-set/vs/scattered%20erasure.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20erasure.xlsx.practice non-unique.png]
|image::benchmarks-set/vs/scattered%20erasure.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20erasure.xlsx.practice non-unique 5.png]
|image::benchmarks-set/vs/scattered erasure.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered erasure.xlsx.practice.png]
|image::benchmarks-set/vs/scattered erasure.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered erasure.xlsx.practice non-unique.png]
|image::benchmarks-set/vs/scattered erasure.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered erasure.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -262,8 +261,8 @@ h|duplicate elements, +
max load factor 5
|
|image::benchmarks-set/vs/scattered%20erasure%20by%20key.xlsx.practice non-unique.png[width=250,link=../diagrams/benchmarks-set/vs/scattered%20erasure%20by%20key.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/vs/scattered%20erasure%20by%20key.xlsx.practice non-unique 5.png[width=250,link=../diagrams/benchmarks-set/vs/scattered%20erasure%20by%20key.xlsx.practice non-unique 5.png,window=_blank]
|image::benchmarks-set/vs/scattered erasure by key.xlsx.practice non-unique.png[width=250,link= _images/benchmarks-set/vs/scattered erasure by key.xlsx.practice non-unique.png,window=_blank]
|image::benchmarks-set/vs/scattered erasure by key.xlsx.practice non-unique 5.png[width=250,link= _images/benchmarks-set/vs/scattered erasure by key.xlsx.practice non-unique 5.png,window=_blank]
|
h|by key, duplicate elements
@ -278,9 +277,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/vs/scattered%20successful%20looukp.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20successful%20looukp.xlsx.practice.png]
|image::benchmarks-set/vs/scattered%20successful%20looukp.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20successful%20looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/vs/scattered%20successful%20looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20successful%20looukp.xlsx.practice non-unique 5.png]
|image::benchmarks-set/vs/scattered successful looukp.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered successful looukp.xlsx.practice.png]
|image::benchmarks-set/vs/scattered successful looukp.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered successful looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/vs/scattered successful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered successful looukp.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -295,9 +294,9 @@ max load factor 5
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-set/vs/scattered%20unsuccessful%20looukp.xlsx.practice.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20unsuccessful%20looukp.xlsx.practice.png]
|image::benchmarks-set/vs/scattered%20unsuccessful%20looukp.xlsx.practice non-unique.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20unsuccessful%20looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/vs/scattered%20unsuccessful%20looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=../diagrams/benchmarks-set/vs/scattered%20unsuccessful%20looukp.xlsx.practice non-unique 5.png]
|image::benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice.png]
|image::benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice non-unique.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice non-unique.png]
|image::benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link= _images/benchmarks-set/vs/scattered unsuccessful looukp.xlsx.practice non-unique 5.png]
h|non-duplicate elements
h|duplicate elements
@ -333,10 +332,10 @@ The unsuccessful lookup benchmarks use `n` randomly generated integers but using
[cols="4*^.^a", frame=all, grid=all]
|===
|image::benchmarks-flat_map/gcc-x64/Running%20insertion.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/gcc-x64/Running%20insertion.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x64/Running%20erasure.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/gcc-x64/Running%20erasure.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x64/Scattered%20successful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/gcc-x64/Scattered%20successful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x64/Scattered%20unsuccessful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/gcc-x64/Scattered%20unsuccessful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x64/Running insertion.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/gcc-x64/Running insertion.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x64/Running erasure.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/gcc-x64/Running erasure.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x64/Scattered successful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/gcc-x64/Scattered successful looukp.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x64/Scattered unsuccessful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/gcc-x64/Scattered unsuccessful looukp.xlsx.plot.png]
h|running insertion
h|running erasure
@ -352,10 +351,10 @@ h|unsuccessful lookup
[cols="4*^.^a", frame=all, grid=all]
|===
|image::benchmarks-flat_map/clang-x64/Running%20insertion.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-x64/Running%20insertion.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x64/Running%20erasure.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-x64/Running%20erasure.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x64/Scattered%20successful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-x64/Scattered%20successful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x64/Scattered%20unsuccessful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-x64/Scattered%20unsuccessful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x64/Running insertion.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-x64/Running insertion.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x64/Running erasure.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-x64/Running erasure.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x64/Scattered successful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-x64/Scattered successful looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x64/Scattered unsuccessful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-x64/Scattered unsuccessful looukp.xlsx.plot.png]
h|running insertion
h|running erasure
@ -371,10 +370,10 @@ h|unsuccessful lookup
[cols="4*^.^a", frame=all, grid=all]
|===
|image::benchmarks-flat_map/vs-x64/Running%20insertion.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/vs-x64/Running%20insertion.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x64/Running%20erasure.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/vs-x64/Running%20erasure.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x64/Scattered%20successful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/vs-x64/Scattered%20successful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x64/Scattered%20unsuccessful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/vs-x64/Scattered%20unsuccessful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x64/Running insertion.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/vs-x64/Running insertion.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x64/Running erasure.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/vs-x64/Running erasure.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x64/Scattered successful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/vs-x64/Scattered successful looukp.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x64/Scattered unsuccessful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/vs-x64/Scattered unsuccessful looukp.xlsx.plot.png]
h|running insertion
h|running erasure
@ -390,10 +389,10 @@ h|unsuccessful lookup
[cols="4*^.^a", frame=all, grid=all]
|===
|image::benchmarks-flat_map/clang-arm64/Running%20insertion.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-arm64/Running%20insertion.xlsx.plot.png]
|image::benchmarks-flat_map/clang-arm64/Running%20erasure.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-arm64/Running%20erasure.xlsx.plot.png]
|image::benchmarks-flat_map/clang-arm64/Scattered%20successful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-arm64/Scattered%20successful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-arm64/Scattered%20unsuccessful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-arm64/Scattered%20unsuccessful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-arm64/Running insertion.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-arm64/Running insertion.xlsx.plot.png]
|image::benchmarks-flat_map/clang-arm64/Running erasure.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-arm64/Running erasure.xlsx.plot.png]
|image::benchmarks-flat_map/clang-arm64/Scattered successful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-arm64/Scattered successful looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-arm64/Scattered unsuccessful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-arm64/Scattered unsuccessful looukp.xlsx.plot.png]
h|running insertion
h|running erasure
@ -409,10 +408,10 @@ h|unsuccessful lookup
[cols="4*^.^a", frame=all, grid=all]
|===
|image::benchmarks-flat_map/gcc-x86/Running%20insertion.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/gcc-x86/Running%20insertion.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x86/Running%20erasure.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/gcc-x86/Running%20erasure.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x86/Scattered%20successful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/gcc-x86/Scattered%20successful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x86/Scattered%20unsuccessful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/gcc-x86/Scattered%20unsuccessful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x86/Running insertion.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/gcc-x86/Running insertion.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x86/Running erasure.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/gcc-x86/Running erasure.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x86/Scattered successful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/gcc-x86/Scattered successful looukp.xlsx.plot.png]
|image::benchmarks-flat_map/gcc-x86/Scattered unsuccessful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/gcc-x86/Scattered unsuccessful looukp.xlsx.plot.png]
h|running insertion
h|running erasure
@ -428,10 +427,10 @@ h|unsuccessful lookup
[cols="4*^.^a", frame=all, grid=all]
|===
|image::benchmarks-flat_map/clang-x86/Running%20insertion.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-x86/Running%20insertion.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x86/Running%20erasure.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-x86/Running%20erasure.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x86/Scattered%20successful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-x86/Scattered%20successful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x86/Scattered%20unsuccessful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/clang-x86/Scattered%20unsuccessful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x86/Running insertion.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-x86/Running insertion.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x86/Running erasure.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-x86/Running erasure.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x86/Scattered successful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-x86/Scattered successful looukp.xlsx.plot.png]
|image::benchmarks-flat_map/clang-x86/Scattered unsuccessful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/clang-x86/Scattered unsuccessful looukp.xlsx.plot.png]
h|running insertion
h|running erasure
@ -447,10 +446,10 @@ h|unsuccessful lookup
[cols="4*^.^a", frame=all, grid=all]
|===
|image::benchmarks-flat_map/vs-x86/Running%20insertion.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/vs-x86/Running%20insertion.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x86/Running%20erasure.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/vs-x86/Running%20erasure.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x86/Scattered%20successful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/vs-x86/Scattered%20successful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x86/Scattered%20unsuccessful%20looukp.xlsx.plot.png[width=250,window=_blank,link=../diagrams/benchmarks-flat_map/vs-x86/Scattered%20unsuccessful%20looukp.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x86/Running insertion.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/vs-x86/Running insertion.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x86/Running erasure.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/vs-x86/Running erasure.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x86/Scattered successful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/vs-x86/Scattered successful looukp.xlsx.plot.png]
|image::benchmarks-flat_map/vs-x86/Scattered unsuccessful looukp.xlsx.plot.png[width=250,window=_blank,link= _images/benchmarks-flat_map/vs-x86/Scattered unsuccessful looukp.xlsx.plot.png]
h|running insertion
h|running erasure
@ -476,9 +475,9 @@ operations follow a https://en.wikipedia.org/wiki/Zipf%27s_law#Formal_definition
with different _skew_ parameters: the higher the skew, the more concentrated are the keys in the lower values
of the covered range.
`boost::concurrent_flat_map` and `boost::concurrent_node_map` are exercised using both regular and xref:#concurrent_bulk_visitation[bulk visitation]:
`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:#concurrent_flat_map_constants[`bulk_visit_size`].
once each time the buffer reaches `xref:reference/concurrent_flat_map.adoc#concurrent_flat_map_constants[bulk_visit_size]`.
=== GCC 12, x64
@ -487,9 +486,9 @@ once each time the buffer reaches xref:#concurrent_flat_map_constants[`bulk_visi
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.500k%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.500k%2C%200.01.png]
|image::benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.500k%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.500k%2C%200.5.png]
|image::benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.500k%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.500k%2C%200.99.png]
|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]
|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]
|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]
h|500k updates, 4.5M lookups +
skew=0.01
@ -503,9 +502,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.5M%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.5M%2C%200.01.png]
|image::benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.5M%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.5M%2C%200.5.png]
|image::benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.5M%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x64/Parallel%20workload.xlsx.5M%2C%200.99.png]
|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]
|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]
|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]
h|5M updates, 45M lookups +
skew=0.01
@ -522,9 +521,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.500k%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.500k%2C%200.01.png]
|image::benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.500k%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.500k%2C%200.5.png]
|image::benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.500k%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.500k%2C%200.99.png]
|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]
|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]
|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]
h|500k updates, 4.5M lookups +
skew=0.01
@ -538,9 +537,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.5M%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.5M%2C%200.01.png]
|image::benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.5M%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.5M%2C%200.5.png]
|image::benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.5M%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x64/Parallel%20workload.xlsx.5M%2C%200.99.png]
|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]
|image::benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.5.png]
|image::benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.99.png]
h|5M updates, 45M lookups +
skew=0.01
@ -557,9 +556,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.500k%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.500k%2C%200.01.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.500k%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.500k%2C%200.5.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.500k%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.500k%2C%200.99.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.500k, 0.01.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.500k, 0.5.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.500k, 0.99.png]
h|500k updates, 4.5M lookups +
skew=0.01
@ -573,9 +572,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.5M%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.5M%2C%200.01.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.5M%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.5M%2C%200.5.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.5M%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x64/Parallel%20workload.xlsx.5M%2C%200.99.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.01.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.5.png]
|image::benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.99.png]
h|5M updates, 45M lookups +
skew=0.01
@ -592,9 +591,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.500k%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.500k%2C%200.01.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.500k%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.500k%2C%200.5.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.500k%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.500k%2C%200.99.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.01.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.5.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.99.png]
h|500k updates, 4.5M lookups +
skew=0.01
@ -608,9 +607,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.5M%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.5M%2C%200.01.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.5M%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.5M%2C%200.5.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.5M%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-arm64/Parallel%20workload.xlsx.5M%2C%200.99.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.01.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.5.png]
|image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.99.png]
h|5M updates, 45M lookups +
skew=0.01
@ -627,9 +626,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.500k%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.500k%2C%200.01.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.500k%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.500k%2C%200.5.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.500k%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.500k%2C%200.99.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.500k, 0.01.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.500k, 0.5.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.500k, 0.99.png]
h|500k updates, 4.5M lookups +
skew=0.01
@ -643,9 +642,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.5M%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.5M%2C%200.01.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.5M%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.5M%2C%200.5.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.5M%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/gcc-x86/Parallel%20workload.xlsx.5M%2C%200.99.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.5M, 0.01.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.5M, 0.5.png]
|image::benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/gcc-x86/Parallel workload.xlsx.5M, 0.99.png]
h|5M updates, 45M lookups +
skew=0.01
@ -662,9 +661,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.500k%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.500k%2C%200.01.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.500k%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.500k%2C%200.5.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.500k%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.500k%2C%200.99.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.500k, 0.01.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.500k, 0.5.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.500k, 0.99.png]
h|500k updates, 4.5M lookups +
skew=0.01
@ -678,9 +677,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.5M%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.5M%2C%200.01.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.5M%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.5M%2C%200.5.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.5M%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/clang-x86/Parallel%20workload.xlsx.5M%2C%200.99.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.5M, 0.01.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.5M, 0.5.png]
|image::benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/clang-x86/Parallel workload.xlsx.5M, 0.99.png]
h|5M updates, 45M lookups +
skew=0.01
@ -697,9 +696,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.500k%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.500k%2C%200.01.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.500k%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.500k%2C%200.5.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.500k%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.500k%2C%200.99.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.01.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.5.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.99.png]
h|500k updates, 4.5M lookups +
skew=0.01
@ -713,9 +712,9 @@ skew=0.99
[cols="3*^.^a", frame=all, grid=all]
|===
|image::benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.5M%2C%200.01.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.5M%2C%200.01.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.5M%2C%200.5.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.5M%2C%200.5.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.5M%2C%200.99.png[width=250,window=_blank,link=../diagrams/benchmarks-concurrent_map/vs-x86/Parallel%20workload.xlsx.5M%2C%200.99.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.5M, 0.01.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.5M, 0.5.png]
|image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link= _images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.5M, 0.99.png]
h|5M updates, 45M lookups +
skew=0.01

3
doc/modules/ROOT/pages/buckets.adoc
View File

@ -1,6 +1,5 @@
[#buckets]
:idprefix: buckets_
:imagesdir: ../diagrams
= Basics of Hash Tables
@ -146,5 +145,3 @@ have a <<unordered_flat_map,`boost::unordered_flat_map`>> with `size()` almost
at `max_load()` level and then erase 1,000 elements, `max_load()` may decrease by around a
few dozen elements. This is done internally by Boost.Unordered in order
to keep its performance stable, and must be taken into account when planning for rehash-free insertions.

4
doc/modules/ROOT/pages/changes.adoc
View File

@ -296,7 +296,7 @@ when the returned proxy is not used.
This is major change which has been converted to use Boost.Move's move
emulation, and be more compliant with the {cpp}11 standard. See the
xref:unordered.adoc#compliance[compliance section] for details.
xref:compliance.adoc[compliance section] for details.
The container now meets {cpp}11's complexity requirements, but to do so
uses a little more memory. This means that `quick_erase` and
@ -456,5 +456,3 @@ many of the suggestions from the review.
Initial review version, for the review conducted from 7th December 2007 to
16th December 2007.

2
doc/modules/ROOT/pages/compliance.adoc
View File

@ -145,6 +145,6 @@ explicit const visitation); In the case of `boost::concurrent_flat_set`, visitat
One notable operation not provided by `boost::concurrent_flat_map`/`boost::concurrent_node_map`
is `operator[]`/`at`, which can be
replaced, if in a more convoluted manner, by
xref:#concurrent_flat_map_try_emplace_or_cvisit[`try_emplace_or_visit`].
`xref:reference/concurrent_flat_map.adoc#concurrent_flat_map_try_emplace_or_cvisit[try_emplace_or_visit]`.
//-

10
doc/modules/ROOT/pages/concurrent.adoc
View File

@ -150,10 +150,10 @@ element already exists):
----
Consult the references of
xref:#concurrent_node_set[`boost::concurrent_node_set`],
xref:#concurrent_flat_map[`boost::concurrent_node_map`],
xref:#concurrent_flat_set[`boost::concurrent_flat_set`] and
xref:#concurrent_flat_map[`boost::concurrent_flat_map`]
`xref:reference/concurrent_node_set#concurrent_node_set[boost::concurrent_node_set]`,
`xref:reference/concurrent_node_map#concurrent_flat_map[boost::concurrent_node_map]`,
`xref:reference/concurrent_flat_set#concurrent_flat_set[boost::concurrent_flat_set]` and
`xref:reference/concurrent_flat_map#concurrent_flat_map[boost::concurrent_flat_map]`
for the complete list of visitation-enabled operations.
== Whole-Table Visitation
@ -237,7 +237,7 @@ m.visit(keys.begin(), keys.end(), [](auto& x) { ++x.second; });
This functionality is not provided for mere syntactic convenience, though: by processing all the
keys at once, some internal optimizations can be applied that increase
performance over the regular, one-at-a-time case (consult the
xref:#benchmarks_boostconcurrent_flat_map[benchmarks]). In fact, it may be beneficial
xref:benchmarks.adoc#benchmarks_boostconcurrent_flatnode_map[benchmarks]). In fact, it may be beneficial
to buffer incoming keys so that they can be bulk visited in chunks:
[source,c++]

2
doc/modules/ROOT/pages/debuggability.adoc
View File

@ -74,7 +74,7 @@ The other containers are identical other than replacing "`boost::unordered_{map|
Both the SIMD and the non-SIMD implementations are viewable through the GDB pretty-printers.
For open-addressing containers where xref:#hash_quality_container_statistics[container statistics] are enabled, you can obtain these statistics by calling `get_stats()` on the container, from within GDB. This is overridden in GDB as an link:https://sourceware.org/gdb/current/onlinedocs/gdb.html/Xmethod-API.html[xmethod], so it will not invoke any C++ synchronization code. See the following printout as an example for the expected format.
For open-addressing containers where xref:hash_quality.adoc#hash_quality_container_statistics[container statistics] are enabled, you can obtain these statistics by calling `get_stats()` on the container, from within GDB. This is overridden in GDB as an link:https://sourceware.org/gdb/current/onlinedocs/gdb.html/Xmethod-API.html[xmethod], so it will not invoke any C++ synchronization code. See the following printout as an example for the expected format.
```plaintext
(gdb) print example_flat_map.get_stats()

12
doc/modules/ROOT/pages/hash_equality.adoc
View File

@ -9,7 +9,7 @@ elements are stored, the unordered associative containers use an equality
predicate and a hash function. For example, <<unordered_map,boost::unordered_map>>
is declared as:
```
```cpp
template <
class Key, class Mapped,
class Hash = boost::hash<Key>,
@ -22,7 +22,7 @@ The hash function comes first as you might want to change the hash function
but not the equality predicate. For example, if you wanted to use the
https://en.wikipedia.org/wiki/Fowler%E2%80%93Noll%E2%80%93Vo_hash_function#FNV-1a_hash[FNV-1a hash^] you could write:
```
```cpp
boost::unordered_map<std::string, int, hash::fnv_1a>
dictionary;
```
@ -31,7 +31,7 @@ There is an link:../../examples/fnv1.hpp[implementation of FNV-1a^] in the examp
If you wish to use a different equality function, you will also need to use a matching hash function. For example, to implement a case insensitive dictionary you need to define a case insensitive equality predicate and hash function:
```
```cpp
struct iequal_to
{
bool operator()(std::string const& x,
@ -60,7 +60,7 @@ struct ihash
```
Which you can then use in a case insensitive dictionary:
```
```cpp
boost::unordered_map<std::string, int, ihash, iequal_to>
idictionary;
```
@ -80,7 +80,7 @@ equality predicate (e.g. `boost::function`) then you can get into trouble.
Similarly, a custom hash function can be used for custom types:
```
```cpp
struct point {
int x;
int y;
@ -108,7 +108,7 @@ boost::unordered_multiset<point, point_hash> points;
Since the default hash function is link:../../../container_hash/index.html[Boost.Hash^],
we can extend it to support the type so that the hash function doesn't need to be explicitly given:
```
```cpp
struct point {
int x;
int y;

4
doc/modules/ROOT/pages/hash_quality.adoc
View File

@ -43,7 +43,7 @@ struct my_string_hash_function
----
By setting the
xref:#hash_traits_hash_is_avalanching[hash_is_avalanching] trait, we inform Boost.Unordered
`xref:reference/hash_traits.adoc#hash_traits_hash_is_avalanching[hash_is_avalanching]` trait, we inform Boost.Unordered
that `my_string_hash_function` is of sufficient quality to be used directly without
any post-mixing safety net. This comes at the risk of degraded performance in the
cases where the hash function is not as well-behaved as we've declared.
@ -108,7 +108,7 @@ Statistics for three internal operations are maintained: insertions (without con
the previous lookup to determine that the key is not present yet), successful lookups,
and unsuccessful lookups (including those issued internally when inserting elements).
_Probe length_ is the number of
xref:#structures_open_addressing_containers[bucket groups] accessed per operation.
xref:structures.adoc#structures_open_addressing_containers[bucket groups] accessed per operation.
If the hash function behaves properly:
* Average probe lengths should be close to 1.0.

3
doc/modules/ROOT/pages/rationale.adoc
View File

@ -130,7 +130,7 @@ concurrent scenarios.
with minimal locking. In particular, the metadata array can be used for implementations of
lookup that are lock-free up to the last step of actual element comparison.
* Layout compatibility with Boost.Unordered flat containers allows for
xref:#concurrent_interoperability_with_non_concurrent_containers[fast transfer]
xref:concurrent.adoc#concurrent_interoperability_with_non_concurrent_containers[fast transfer]
of all elements between a concurrent container and its non-concurrent counterpart,
and vice versa.
@ -140,4 +140,3 @@ Concurrent containers make the same decisions and provide the same guarantees
as Boost.Unordered open-addressing containers with regards to
xref:#rationale_hash_function[hash function defaults] and
xref:#rationale_platform_interoperability[platform interoperability].

28
doc/modules/ROOT/pages/ref.adoc
View File

@ -1,17 +1,17 @@
[#reference]
= Reference
include::unordered_map.adoc[]
include::unordered_multimap.adoc[]
include::unordered_set.adoc[]
include::unordered_multiset.adoc[]
include::hash_traits.adoc[]
include::stats.adoc[]
include::unordered_flat_map.adoc[]
include::unordered_flat_set.adoc[]
include::unordered_node_map.adoc[]
include::unordered_node_set.adoc[]
include::concurrent_flat_map.adoc[]
include::concurrent_flat_set.adoc[]
include::concurrent_node_map.adoc[]
include::concurrent_node_set.adoc[]
* xref:reference/unordered_map.adoc[unordered_map]
* xref:reference/unordered_multimap.adoc[unordered_multimap]
* xref:reference/unordered_set.adoc[unordered_set]
* xref:reference/unordered_multiset.adoc[unordered_multiset]
* xref:reference/hash_traits.adoc[hash_traits]
* xref:reference/stats.adoc[stats]
* xref:reference/unordered_flat_map.adoc[unordered_flat_map]
* xref:reference/unordered_flat_set.adoc[unordered_flat_set]
* xref:reference/unordered_node_map.adoc[unordered_node_map]
* xref:reference/unordered_node_set.adoc[unordered_node_set]
* xref:reference/concurrent_flat_map.adoc[concurrent_flat_map]
* xref:reference/concurrent_flat_set.adoc[concurrent_flat_set]
* xref:reference/concurrent_node_map.adoc[concurrent_node_map]
* xref:reference/concurrent_node_set.adoc[concurrent_node_set]

2
doc/modules/ROOT/pages/regular.adoc
View File

@ -10,7 +10,7 @@ C++ specification for unordered associative containers, so for those who know ho
drop-in replacements. The interface of open-addressing containers (`boost::unordered_node_set`,
`boost::unordered_node_map`, `boost::unordered_flat_set` and `boost::unordered_flat_map`)
is very similar, but they present some minor differences listed in the dedicated
xref:#compliance_open_addressing_containers[standard compliance section].
xref:compliance.adoc#compliance_open_addressing_containers[standard compliance section].
For readers without previous experience with hash containers but familiar

10
doc/modules/ROOT/pages/structures.adoc
View File

@ -25,7 +25,7 @@ Canonical standard implementations will wind up looking like the diagram below:
[.text-center]
.The canonical standard approach
image::singly-linked.png[align=center,link=../diagrams/singly-linked.png,window=_blank]
image::singly-linked.png[align=center,link=_images/singly-linked.png,window=_blank]
It's worth noting that this approach is only used by pass:[libc++] and pass:[libstdc++]; the MSVC Dinkumware implementation uses a different one. A more detailed analysis of the standard containers can be found http://bannalia.blogspot.com/2013/10/implementation-of-c-unordered.html[here].
@ -63,7 +63,7 @@ A more detailed description of Boost.Unordered's closed-addressing implementatio
given in an
https://bannalia.blogspot.com/2022/06/advancing-state-of-art-for.html[external article].
For more information on implementation rationale, read the
xref:#rationale_closed_addressing_containers[corresponding section].
xref:rationale.adoc#rationale_open_addresing_containers[corresponding section].
== Open-addressing Containers
@ -125,13 +125,13 @@ A more detailed description of Boost.Unordered's open-addressing implementation
given in an
https://bannalia.blogspot.com/2022/11/inside-boostunorderedflatmap.html[external article].
For more information on implementation rationale, read the
xref:#rationale_open_addresing_containers[corresponding section].
xref:rationale.adoc#rationale_open_addresing_containers[corresponding section].
== Concurrent Containers
`boost::concurrent_flat_set`/`boost::concurrent_node_set` and
`boost::concurrent_flat_map`/`boost::concurrent_node_map` use the basic
xref:#structures_open_addressing_containers[open-addressing layout] described above
xref:structures.adoc#structures_open_addressing_containers[open-addressing layout] described above
augmented with synchronization mechanisms.
@ -177,4 +177,4 @@ practice, the start-over frequency is extremely small, measured in the range
of parts per million for some of our benchmarks.
For more information on implementation rationale, read the
xref:#rationale_concurrent_containers[corresponding section].
xref:rationale.adoc#rationale_concurrent_containers[corresponding section].