qc-hash
Extremely fast unordered map and set library for C++20 (by Daskie)
hashtable-bench
A benchmark for hash tables and hash functions in C++, evaluate on different data as comprehensively as possible (by renzibei)
| qc-hash | hashtable-bench | |
|---|---|---|
| 1 | 1 | |
| 10 | 12 | |
| - | - | |
| 5.7 | 1.7 | |
| 8 months ago | 12 months ago | |
| C++ | Jupyter Notebook | |
| MIT License | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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.
qc-hash
Posts with mentions or reviews of qc-hash.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-16.
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.
What are some alternatives?
When comparing qc-hash and hashtable-bench you can also consider the following projects:
CppPerformanceBenchmarks
eytzinger - Cache-friendly associative STL-like container with an Eytzinger (BFS) layout for C++
dense_hash_map - A simple replacement for std::unordered_map
fph-table - Flash Perfect Hash Table: an implementation of a dynamic perfect hash table, extremely fast for lookup
gtl - Greg's Template Library of useful classes.
google-sparsehash - Clone of google-sparsehash
llvm-project - The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
recursive-variant - Recursive Variant: A simple library for Recursive Variant Types
qc-hash vs CppPerformanceBenchmarks
hashtable-bench vs eytzinger
qc-hash vs dense_hash_map
hashtable-bench vs CppPerformanceBenchmarks
qc-hash vs fph-table
hashtable-bench vs gtl
qc-hash vs google-sparsehash
hashtable-bench vs llvm-project
qc-hash vs recursive-variant
hashtable-bench vs dense_hash_map
qc-hash vs eytzinger
hashtable-bench vs fph-table