hashtable-bench
A benchmark for hash tables and hash functions in C++, evaluate on different data as comprehensively as possible (by renzibei)
gtl
Greg's Template Library of useful classes. (by greg7mdp)
hashtable-bench | gtl | |
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1 | 5 | |
12 | 90 | |
- | - | |
1.7 | 7.1 | |
12 months ago | 29 days ago | |
Jupyter Notebook | C++ | |
- | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
hashtable-bench
Posts with mentions or reviews of hashtable-bench.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-16.
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Updating map_benchmarks: Send your hashmaps!
I believe that when the number of elements is larger than 4 (a rough estimation), the associative linear table won't be faster than ska::flat_hash_map or fph-table with the identity hash function. If you look at the benchmark results, you will find that the average lookup time may well be less than 2 nanoseconds when item number is smaller than one thousand on morden CPUs. For these two hash tables, there are only about ten instructions in the critical path of lookup. And this should be faster than the linear search in a associative table, where there are a lot of branches and comparing instructions. However, you should benchmark it youself to get the real conclusion. This is just a simple analysis on paper from mine. By the way, the associative table can be faster if it is implemented with hardware circuits or SIMD instructions.
gtl
Posts with mentions or reviews of gtl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-07.
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Inside boost::concurrent_flat_map
gtl library author here. Very nice writeup! Reading it made me think, and I believe I know why gtl::parallel_flat_hash_map performs comparatively worse for high-skew scenarios (just pushed a fix in gtl).
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Boost 1.81 will have boost::unordered_flat_map...
I do this as well in my phmap and gtl implementations. It makes the tables look worse in benchmarks like the above, but prevents really bad surprises occasionally.
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Comprehensive C++ Hashmap Benchmarks 2022
Thanks a lot for the great benchmark, Martin. Glad you used different hash functions, because I do sacrifice some speed to make sure that the performance of my hash maps doesn't degrade drastically with poor hash functions. Happy to see that my phmap and gtl (the C++20 version) performed well.
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It is now trivial to cache pure functions with highly efficient, concurrent cache.
This is very easy to do with the latest version of gtl. And it is extremely efficient, as the caching mechanism uses the parallel hashmap, which internally is divided into N submaps each with its own mutex, reducing mutex contention to a minimum.
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Updating map_benchmarks: Send your hashmaps!
AFAIK sparsepp has been dropped entirely in favor of the containers in GTL: https://github.com/greg7mdp/gtl
What are some alternatives?
When comparing hashtable-bench and gtl you can also consider the following projects:
eytzinger - Cache-friendly associative STL-like container with an Eytzinger (BFS) layout for C++
CppPerformanceBenchmarks
fph-table - Flash Perfect Hash Table: an implementation of a dynamic perfect hash table, extremely fast for lookup
llvm-project - The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
Google Test - GoogleTest - Google Testing and Mocking Framework
dense_hash_map - A simple replacement for std::unordered_map
flat_hash_map - A very fast hashtable
qc-hash - Extremely fast unordered map and set library for C++20
google-sparsehash - Clone of google-sparsehash
libcudacxx - [ARCHIVED] The C++ Standard Library for your entire system. See https://github.com/NVIDIA/cccl
hashtable-bench vs eytzinger
gtl vs eytzinger
hashtable-bench vs CppPerformanceBenchmarks
gtl vs fph-table
hashtable-bench vs llvm-project
gtl vs Google Test
hashtable-bench vs dense_hash_map
gtl vs flat_hash_map
hashtable-bench vs qc-hash
gtl vs google-sparsehash
hashtable-bench vs fph-table
gtl vs libcudacxx