eigen
parallel-hashmap
eigen | parallel-hashmap | |
---|---|---|
19 | 34 | |
- | 2,896 | |
- | 3.9% | |
- | 7.3 | |
- | about 1 month ago | |
C++ | ||
- | Apache License 2.0 |
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.
eigen
-
Blaze: A High Performance C++ Math library
Is Eigen still alive? There's been no release in 3 years, and no news about it: https://gitlab.com/libeigen/eigen/-/issues/2699
- Gentoo -Os vs -O3 application startup time?
-
The Case of the Missing SIMD Code
I was curious about these libraries a few weeks ago and did some searching. Is there one that's got a clearly dominating set of users or contributors?
I don't know what a good way to compare these might be, other than perhaps activity/contributor count.
[1] https://github.com/simd-everywhere/simde
[2] https://github.com/ermig1979/Simd
[3] https://github.com/google/highway
[4] https://gitlab.com/libeigen/eigen
[5] https://github.com/shibatch/sleef
-
FetchContent and PROJECT_IS_TOP_LEVEL
I am trying to include Eigen in my project via FetchContent. They define/assume-defined PROJECT_IS_TOP_LEVEL on line 19 and, among other locations, on line 607 in their top level list file.
-
Common practices when doing image processing on the GPU
Eigen is a header-only library, thus simply cloning it from the official repository into the FOGGDD folder should be enough.
- Use TFlite in a Cmake Project
-
I've decided to learn Godot and it feels like I have "lost"
math library because you should never implement a math library yourself, and you probably want somethign more focused on performance than STL. GLM may work if you just need basic vector support. Eigen may help for a more physics heavy game. But I'd probably find something in-between those two
-
CMake: How to include the headers of an external library downloaded with FetchContent?
cmake_minimum_required(VERSION 3.15) project(app) include(FetchContent) FetchContent_Declare(Eigen3 URL https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4.0.tar.gz) FetchContent_MakeAvailable(Eigen3) add_executable(app main.cpp) target_link_libraries(app Eigen3::Eigen)
-
-🎄- 2021 Day 13 Solutions -🎄-
Today was very easy to do with Eigen
- The official Eigen repo is now back online
parallel-hashmap
-
Parallel-hashmap: drop-in replacement for unordered_map, unordered_set
My default they are not thread safe, i.e., they offer the same thread safety as std::map or any stdlib type; however, the map can optionally be made thread safe and is apparently optimized for this usage. Details at: https://github.com/greg7mdp/parallel-hashmap?tab=readme-ov-f....
-
Designing a Fast Concurrent Hash Table
This looks pretty good in terms of its tradeoffs and tricks used. Makes good use of the Metadata, as in https://greg7mdp.github.io/parallel-hashmap/
-
The One Billion Row Challenge in CUDA: from 17 minutes to 17 seconds
Standard library maps/unordered_maps are themselves notoriously slow anyway. A sparse_hash_map from abseil or parallel-hashmaps[1] would be better.
[1] https://github.com/greg7mdp/parallel-hashmap
-
My own Concurrent Hash Map picks
Cool! Looking forward to you trying my phmap - and please let me know if you have any question.
-
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.
-
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.
-
Can C++ maps be as efficient as Python dictionaries ?
I use https://github.com/greg7mdp/parallel-hashmap when I need better performance of maps and sets.
-
How to build a Chess Engine, an interactive guide
Then they should really try https://github.com/greg7mdp/parallel-hashmap, the current state of the art.
- boost::unordered map is a new king of data structures
-
Is A* just always slow?
std::unordered_map is notorious for being slow. Use a better implementation (I like the flat naps from here, which are the same as abseil’s). The question that needs to be asked too is if you need to use a map.
What are some alternatives?
NumCpp - C++ implementation of the Python Numpy library
Folly - An open-source C++ library developed and used at Facebook.
mathfu - C++ math library developed primarily for games focused on simplicity and efficiency.
flat_hash_map - A very fast hashtable
learn-gdscript - Learn Godot's GDScript programming language from zero, right in your browser, for free.
robin-hood-hashing - Fast & memory efficient hashtable based on robin hood hashing for C++11/14/17/20