Cache-friendly associative container with an Eytzinger layout for C++11/14/17

fixed_eytzinger_map is a free implementation of Eytzinger’s layout, in a form of an STL-like generic associative container, broadly compatible with a well-established access patterns.

An Eytzinger map, or BFS(breadth-first search) map, places elements in a lookup order, which leads to a better memory locality. In practice, such container can outperform searching in sorted arrays, like boost::flat_map, due to less cache misses made in a lookup process. In comparison with RB-based trees, like std::map, lookup in Eytzinger map can be multiple times faster. Some comparison graphs are given here.

Unlike std- or boost- associative containers, fixed_eytzinger_map can't be modified after initial construction. This limitation comes from it's layout principle and an inability to alter it with any bearable complexity. It's content can be assigned or swapped in a transaction-like manner, but no per-key alterations are allowed.

fixed_eytzinger_map supports heterogeneous lookup, either with std::less<> or using a custom comparator with an is_transparent tag.

fixed_eytzinger_map comes in a form of a single header with no dependencies. This implementation is platform and architecture agnostic, it's being tested on clang/gcc/cl on x86 and x86-64. Just drop fixed_eytzinger_map/include/fixed_eytzinger_map.h to some reachable place and include this header:

#include <iostream>
#include <string>
#include <numeric>
#include <fixed_eytzinger_map.h>
using namespace std;
int main()
{
   fixed_eytzinger_map<int, string> m{{
      {0, "Hello"}, {1, ","}, {2, " "}, {3, "World"}, {4, "!"}, {5, "\n"} }};

   for( int i = 0; i <= 5; ++i )
      cout << m[i];

   cout << "strlen = " << accumulate(begin(m), end(m), 0, [](int s, const auto &i){
      return s + i.second.size(); }) << endl;

   cout << "keys order: " << accumulate(begin(m), end(m), ""s, [](string s, const auto &i){
      return s + to_string(i.first) + " "; }) << endl;
}

Output:

Hello, World!
strlen = 14
keys order: 3 1 5 0 2 4 

Rationale and design notes: https://kazakov.life/2017/03/06/cache-friendly-associative-container/

Thorough explanation of a lookup behaviour: http://bannalia.blogspot.com/2015/06/cache-friendly-binary-search.html

Academic work on different array layouts: https://arxiv.org/ftp/arxiv/papers/1509/1509.05053.pdf