stl-header-heft
stdBLAS
| stl-header-heft | stdBLAS | |
|---|---|---|
| 5 | 4 | |
| 53 | 103 | |
| - | 7.8% | |
| 0.0 | 3.3 | |
| over 3 years ago | about 1 month ago | |
| Python | C++ | |
| - | GNU General Public License v3.0 or later |
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.
stl-header-heft
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"Fast Kernel Headers" Tree -v1: Eliminate the Linux kernel's "Dependency Hell"
The older I get the more I think #include in public headers needs to have a whitelisted regex git push filter, and the permitted whitelist of permitted includes is small and excludes most of the standard library. https://github.com/ned14/stl-header-heft, after all.
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C++23: Near The Finish Line
As you know, every two years or so I update https://github.com/ned14/stl-header-heft and historically the only STL to shrink in terms of token count has been yours, albeit starting from a high initial base. libstdc++ consistently grows. I look forward to discovering how VS2022's STL compares to preceding editions.
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C++ Library Include Times: Time it takes to #include any standard library and other headers
You may want to have a look at https://github.com/ned14/stl-header-heft too :)
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zpp::throwing<T> - Implementing "almost" C++ exceptions with coroutines
string_view drags in a ton of the STL. string_view cannot deallocate on destruction. See https://github.com/ned14/stl-header-heft.
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Why is this channel less active?
Even million line C++ codebases can compile from scratch within minutes if your header files never include anything not in the least impact headers list from https://github.com/ned14/stl-header-heft.
stdBLAS
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Which is the best way to work with matrices and linear algebra using c++?
You can have a look at https://github.com/kokkos/stdBLAS (it's an implementation of the proposed linear algebra extensions for future C++).
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C++23: Near The Finish Line
It has the same BSD license as Kokkos: https://github.com/kokkos/stdBLAS/blob/main/LICENSE
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Linear Algebra Library Reccomendations?
The BLAS and LAPACK have C interfaces, and they generally don't allocate memory unless you ask them. (Some BLAS implementations allocate internal storage for rearranging matrix data.) There are a few C++ BLAS wrappers; here is one of them.
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Is there an OOP-wrapper library for cublas?
The second one is stdBLAS by kokkos. It doesn't even use cuBLAS but it's a reference implementation of P1673. This paper describe what could be a blas API in the std. I would recommend trying to do something equivalent on your side.
What are some alternatives?
papers - ISO/IEC JTC1 SC22 WG21 paper scheduling and management
mdspan - Reference implementation of mdspan targeting C++23
papers
kokkos - Kokkos C++ Performance Portability Programming Ecosystem: The Programming Model - Parallel Execution and Memory Abstraction
include-what-you-use - A tool for use with clang to analyze #includes in C and C++ source files
plf_hive - plf::hive is a fork of plf::colony to match the current C++ standards proposal.
plf_colony - An unordered C++ data container providing fast iteration/insertion/erasure while maintaining pointer/iterator validity to non-erased elements regardless of insertions/erasures. Provides higher-performance than std:: library containers for high-modification scenarios with unordered data.
LEWG - Project planning for the C++ Library Evolution Working Group
zapcc - zapcc is a caching C++ compiler based on clang, designed to perform faster compilations
zpp_throwing - Using coroutines to implement C++ exceptions for freestanding environments