GLM
OpenBLAS
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GLM | OpenBLAS | |
---|---|---|
36 | 22 | |
8,653 | 5,933 | |
2.0% | 2.0% | |
9.0 | 9.8 | |
3 days ago | 5 days ago | |
C++ | C | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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.
GLM
- Release of GLM 1.0.0
- C++23: The Next C++ Standard
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What files from glm's github do I need to add to my emscripten project?
I am a greenhorn at graphics programming. I just made an app in OpenGL with C++ that I now need to change over to a browser app with WebGL. WebGL looks pretty cool but since my app does a lot of calculations I assumed I should keep the heavier calculating parts in C++ with emscripten ( which I am also just learning ). So looking at it, it just looks like glm is the only library I seriously need for my c++ code and that seems pretty cool because it is a header only app it says. But in the github there are a lot of folders and files so I am not sure which are indispensable or not. Any advice?
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What is a file with the .i.hh extension such as myfile.i.hh used for in a C++ project?
GLM does it quite well, it has core includes then a detail folder with all the inl files that get added. https://github.com/g-truc/glm
- [Opengl] Aide: compilation et installation de GLFW
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Porting to metal?
I once ported an OpenGL code base over to Metal. For me, it was essential to do as much code sharing as possible. Because I was using the GLM library in that code base and generally found that library very useful I wanted to know whether I can use GLM with Metal. I had to do some research but it turned out it works really well, see here
- Which is the best way to work with matrices and linear algebra using c++?
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Best C++ Game Framework
I would also recommend GLM
- PocketPy: A Lightweight(~5000 LOC) Python Implementation in C++17
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Learning DirectX 12 in 2023
Alongside MiniEngine, you’ll want to look into the DirectX Toolkit. This is a set of utilities by Microsoft that simplify graphics and game development. It contains libraries like DirectXMesh for parsing and optimizing meshes for DX12, or DirectXMath which handles 3D math operations like the OpenGL library glm. It also has utilities for gamepad input or sprite fonts. You can see a list of the headers here to get an idea of the features. You’ll definitely want to include this in your project if you don’t want to think about a lot of these solved problems (and don’t have to worry about cross-platform support).
OpenBLAS
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LLaMA Now Goes Faster on CPUs
The Fortran implementation is just a reference implementation. The goal of reference BLAS [0] is to provide relatively simple and easy to understand implementations which demonstrate the interface and are intended to give correct results to test against. Perhaps an exceptional Fortran compiler which doesn't yet exist could generate code which rivals hand (or automatically) tuned optimized BLAS libraries like OpenBLAS [1], MKL [2], ATLAS [3], and those based on BLIS [4], but in practice this is not observed.
Justine observed that the threading model for LLaMA makes it impractical to integrate one of these optimized BLAS libraries, so she wrote her own hand-tuned implementations following the same principles they use.
[0] https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprogra...
[1] https://github.com/OpenMathLib/OpenBLAS
[2] https://www.intel.com/content/www/us/en/developer/tools/onea...
[3] https://en.wikipedia.org/wiki/Automatically_Tuned_Linear_Alg...
- Assume I'm an idiot - oogabooga LLaMa.cpp??!
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Learn x86-64 assembly by writing a GUI from scratch
Yeah. I'm going to be helping to work on expanding CI for OpenBlas and have been diving into this stuff lately. See the discussion in this closed OpenBlas issue gh-1968 [0] for instance. OpenBlas's Skylake kernels do rely on intrinsics [1] for compilers that support them, but there's a wide range of architectures to support, and when hand-tuned assembly kernels work better, that's what are used. For example, [2].
[0] https://github.com/xianyi/OpenBLAS/issues/1968
[1] https://github.com/xianyi/OpenBLAS/blob/develop/kernel/x86_6...
[2] https://github.com/xianyi/OpenBLAS/blob/23693f09a26ffd8b60eb...
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AI’s compute fragmentation: what matrix multiplication teaches us
We'll have to wait until part 2 to see what they are actually proposing, but they are trying to solve a real problem. To get a sense of things check out the handwritten assembly kernels in OpenBlas [0]. Note the level of granularity. There are micro-optimized implementations for specific chipsets.
If progress in ML will be aided by a proliferation of hyper-specialized hardware, then there really is a scalability issue around developing optimized matmul routines for each specialized chip. To be able to develop a custom ASIC for a particular application and then easily generate the necessary matrix libraries without having to write hand-crafted assembly for each specific case seems like it could be very powerful.
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Trying downloading BCML
libraries mkl_rt not found in ['C:\python\lib', 'C:\', 'C:\python\libs'] ``` Install this and try again. Might need to reboot, never know with Windows https://www.openblas.net/
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The Bitter Truth: Python 3.11 vs Cython vs C++ Performance for Simulations
There isn't any fortran code in the repo there itself but numpy itself can be linked with several numeric libraries. If you look through the wheels for numpy available on pypi, all the latest ones are packaged with OpenBLAS which uses Fortran quite a bit: https://github.com/xianyi/OpenBLAS
- Optimizing compilers reload vector constants needlessly
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Just a quick question, can a programming language be as fast as C++ and efficient with as simple syntax like Python?
Sure - write functions in another language, export C bindings, and then call those functions from Python. An example is NumPy - a lot of its linear algebra functions are implemented in C and Fortran.
- OpenBLAS - optimized BLAS library based on GotoBLAS2 1.13 BSD version
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How to include external libraries?
Read the official docs yet?
What are some alternatives?
Eigen
DirectXMath - DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps
cblas - Netlib's C BLAS wrapper: http://www.netlib.org/blas/#_cblas
linmath.h - a lean linear math library, aimed at graphics programming. Supports vec3, vec4, mat4x4 and quaternions
blaze
cglm - 📽 Highly Optimized 2D / 3D Graphics Math (glm) for C
Boost.Multiprecision - Boost.Multiprecision
ceres-solver - A large scale non-linear optimization library
CGal - The public CGAL repository, see the README below