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DirectXMath Alternatives
Similar projects and alternatives to DirectXMath
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LearnOpenGL
Code repository of all OpenGL chapters from the book and its accompanying website https://learnopengl.com
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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DirectXShaderCompiler
This repo hosts the source for the DirectX Shader Compiler which is based on LLVM/Clang.
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crux
Discontinued General purpose bitemporal database for SQL, Datalog & graph queries. Backed by @juxt [Moved to: https://github.com/xtdb/xtdb]
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DirectXTK
The DirectX Tool Kit (aka DirectXTK) is a collection of helper classes for writing DirectX 11.x code in C++
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
DirectXMath reviews and mentions
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Vector math library benchmarks (C++)
For those unfamiliar, like I was, DXM is DirectXMath.
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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).
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Optimizing compilers reload vector constants needlessly
Bad news. For SIMD there are not cross-platform intrinsics. Intel intrinsics map directly to SSE/AVX instructions and ARM intrinsics map directly to NEON instructions.
For cross-platform, your best bet is probably https://github.com/VcDevel/std-simd
There's https://eigen.tuxfamily.org/index.php?title=Main_Page But, it's tremendously complicated for anything other than large-scale linear algebra.
And, there's https://github.com/microsoft/DirectXMath But, it has obvious biases :P
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MATHRIL - Custom math library for game programming
I am not in gamedev, but work with 3D graphics, we use DirectX 11, so DirectXMath was a natural choice, it is header only, it supports SIMD instructions (SSE, AVX, NEON etc.), it can even be used on Linux (has no dependence on Windows). It of course just one choice: https://github.com/Microsoft/DirectXMath.
- When i had to look up what a Quaternion is
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Eigen: A C++ template library for linear algebra
I never really used GLM, but Eigen was substantially slower than DirectXMath https://github.com/microsoft/DirectXMath for these things. Despite the name, 99% of that library is OS agnostic, only a few small pieces (like projection matrix formula) are specific to Direct3D. When enabled with corresponding macros, inline functions from that library normally compile into pretty efficient manually vectorized SSE, AVX or NEON code.
The only major issue, DirectXMath doesn’t support FP64 precision.
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maths - templated c++ linear algebra library with vector swizzling, intersection tests and useful functions for games and graphics dev... includes live webgl/wasm demo ?
If you’re the author, consider comparisons with the industry standards, glm and DirectXMath, which both ensure easy interoperability with the two graphics APIs.
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Algorithms for division: Using Newton's method
Good article, but note that if the hardware supports the division instruction, will be much faster than the described workarounds.
Personally, I recently did what’s written in 2 cases: FP32 division on ARMv7, and FP64 division on GPUs who don’t support that instruction.
For ARM CPUs, not only they have FRECPE, they also have FRECPS for the iteration step. An example there: https://github.com/microsoft/DirectXMath/blob/jan2021/Inc/Di...
For GPUs, Microsoft classified FP64 division as “extended double shader instruction” and the support is optional. However, GPUs are guaranteed to support FP32 division. The result of FP32 division provides an awesome starting point for Newton-Raphson refinement in FP64 precision.
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Use of BLAS vs direct SIMD for linear algebra library operations?
For graphics DX math is a very good library.
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Speeding Up `Atan2f` by 50x
I wonder how does it compare with Microsoft’s implementation, there: https://github.com/microsoft/DirectXMath/blob/jan2021/Inc/Di...
Based on the code your version is probably much faster. It would be interesting to compare precision still, MS uses 17-degree polynomial there.
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microsoft/DirectXMath is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of DirectXMath is C++.
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