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2019-03-31 16:41:49 -04:00
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html/parallel_hashmap.md
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The benefit of this approach would be that the internal tables would each resize on its own when they reach 87.5% capacity, and since each table contains approximately one sixteenth of the values, the memory usage peak would be only one sixteenth of the size we saw for the single *flat_hash_map*.
The rest of this article describes my implementation of this concept that I have done in my [parallel hashmap](https://github.com/greg7mdp/parallel-hashmap) repository. This is a header only library, which provides the following eight hashmaps:
- phmap::flat_hash_set
- phmap::flat_hash_map
- phmap::node_hash_set
- phmap::node_hash_map
- phmap::parallel_flat_hash_set
- phmap::parallel_flat_hash_map
- phmap::parallel_node_hash_set
- phmap::parallel_node_hash_map
- phmap::flat_hash_set
- phmap::flat_hash_map
- phmap::node_hash_set
- phmap::node_hash_map
- phmap::parallel_flat_hash_set
- phmap::parallel_flat_hash_map
- phmap::parallel_node_hash_set
- phmap::parallel_node_hash_map
This implementation requires a C++11 compatible compiler, and provides full compatibility with the std::unordered_map (with the exception of *pointer stability* for the `flat` versions. C++14 and C++17 methods, like `try-emplace`, are provided as well.
The names for it are *parallel_flat_hash_map* or *parallel_flat_hash_set*, and the *node* equivalents. These hashmaps provide the same external API as the *flat_hash_map*, and internally use a std::array of 2**N *flat_hash_maps*.
index.html
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</blockquote>
<p><img src="https://github.com/greg7mdp/parallel-hashmap/blob/master/html/img/index_computation.png?raw=true" alt="index_computation" /></p>
<p>The benefit of this approach would be that the internal tables would each resize on its own when they reach 87.5% capacity, and since each table contains approximately one sixteenth of the values, the memory usage peak would be only one sixteenth of the size we saw for the single <em>flat_hash_map</em>.</p>
<p>The rest of this article describes my implementation of this concept that I have done in my <a href="https://github.com/greg7mdp/parallel-hashmap">parallel hashmap</a> repository. This is a header only library, which provides the following eight hashmaps: - phmap::flat_hash_set - phmap::flat_hash_map - phmap::node_hash_set - phmap::node_hash_map - phmap::parallel_flat_hash_set - phmap::parallel_flat_hash_map - phmap::parallel_node_hash_set - phmap::parallel_node_hash_map</p>
<p>The rest of this article describes my implementation of this concept that I have done in my <a href="https://github.com/greg7mdp/parallel-hashmap">parallel hashmap</a> repository. This is a header only library, which provides the following eight hashmaps:</p>
<ul>
<li>phmap::flat_hash_set</li>
<li>phmap::flat_hash_map</li>
<li>phmap::node_hash_set</li>
<li>phmap::node_hash_map</li>
<li>phmap::parallel_flat_hash_set</li>
<li>phmap::parallel_flat_hash_map</li>
<li>phmap::parallel_node_hash_set</li>
<li>phmap::parallel_node_hash_map</li>
</ul>
<p>This implementation requires a C++11 compatible compiler, and provides full compatibility with the std::unordered_map (with the exception of <em>pointer stability</em> for the <code>flat</code> versions. C++14 and C++17 methods, like <code>try-emplace</code>, are provided as well. The names for it are <em>parallel_flat_hash_map</em> or <em>parallel_flat_hash_set</em>, and the <em>node</em> equivalents. These hashmaps provide the same external API as the <em>flat_hash_map</em>, and internally use a std::array of 2**N <em>flat_hash_maps</em>.</p>
<p>I was delighted to find out that not only the <em>parallel_flat_hash_map</em> has significant memory usage benefits compared to the <em>flat_hash_map</em>, but it also has significant advantages for concurrent programming as I will show later. In the rest of this article, we will focus on the <em>parallel_flat_hash_map</em>, but similar results are seen for the <em>parallel_node_hash_map</em>, and the <em>set</em> versions of course.</p>
<h3 id="the-parallel-hashmap-memory-usage">The Parallel Hashmap: memory usage</h3>