Search Results for "matrix operations"
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Showing 114 open source projects for "matrix operations"
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Book4_Power-of-Matrix
Book_4_Matrix Power | The Iris Book: From Addition, Subtraction
Book4_Power-of-Matrix is an open educational repository that forms part of the Visualize-ML book series, focusing on explaining matrix mathematics and linear algebra concepts through visual and intuitive methods. The project is designed to help readers progress from basic arithmetic toward machine learning fundamentals by building a strong conceptual understanding of vectors, matrices, and their operations. -
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OpenBLAS
Optimized BLAS library based on GotoBLAS2 1.13 BSD version
OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. The BLAS (Basic Linear Algebra Subprograms) are routines that provide standard building blocks for performing basic vector and matrix operations. The Level 1 BLAS performs scalar, vector and vector-vector operations, the Level 2 BLAS performs matrix-vector operations, and the Level 3 BLAS performs matrix-matrix operations. Because the BLAS are efficient, portable, and widely available, they are commonly used in the development of high-quality linear algebra software, LAPACK for example. ... -
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JOML
A Java math library for OpenGL rendering calculations
JOML is a high-performance, lightweight math library designed for 3D graphics applications in Java, particularly those using OpenGL, Vulkan, or LWJGL. It provides a complete suite of vector, matrix, quaternion, and geometry operations essential for real-time graphics and game development. Unlike other math libraries, JOML avoids object allocation during calculations, making it highly optimized for garbage-free performance. With precise control over mathematical operations and compatibility with low-level APIs, JOML is a go-to library for Java developers working on real-time 3D engines and simulations. -
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MatMul-Free LM
Implementation for MatMul-free LM
MatMul-Free LM is an experimental implementation of a large language model architecture designed to eliminate traditional matrix multiplication operations used in transformer networks. Since matrix multiplication is one of the most computationally expensive components of modern language models, the project explores alternative computational strategies that reduce hardware requirements while maintaining comparable performance. The architecture relies on quantization-aware training and lightweight operations to replace conventional dense matrix multiplications with more efficient alternatives. ... -
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glMatrix
Javascript Matrix and Vector library for High Performance WebGL apps
Javascript has evolved into a language capable of handling realtime 3D graphics, via WebGL, and computationally intensive tasks such as physics simulations. These types of applications demand high performance vector and matrix math, which is something that Javascript doesn't provide by default. glMatrix to the rescue! glMatrix is designed to perform vector and matrix operations stupidly fast! By hand-tuning each function for maximum performance and encouraging efficient usage patterns through API conventions, glMatrix will help you get the most out of your browsers Javascript engine. -
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IronCalc
Main engine of the IronCalc ecosystem
IronCalc is a new, modern, work-in-progress spreadsheet engine and set of tools to work with spreadsheets in diverse settings. IronCalc is a lightweight, open-source computational engine designed for performing mathematical operations, formula calculations, and data-driven tasks. -
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HLSL++
Math library using HLSL syntax with multiplatform SIMD support
...It also extends beyond standard HLSL capabilities by introducing additional features such as quaternion support, advanced matrix operations, and extended vector types like float8. The library is particularly valuable for game developers who need consistency between CPU and GPU computations, reducing errors and improving maintainability. -
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DeepGEMM
Clean and efficient FP8 GEMM kernels with fine-grained scaling
DeepGEMM is a specialized CUDA library for efficient, high-performance general matrix multiplication (GEMM) operations, with particular focus on low-precision formats such as FP8 (and experimental support for BF16). The library is designed to work cleanly and simply, avoiding overly templated or heavily abstracted code, while still delivering performance that rivals expert-tuned libraries. It supports both standard and “grouped” GEMMs, which is useful for architectures like Mixture of Experts (MoE) that require segmented matrix multiplications. ... -
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bitsandbytes
Accessible large language models via k-bit quantization for PyTorch
...These optimizations enable large language models and other deep learning architectures to run on hardware with limited memory resources, including consumer-grade GPUs. The project includes specialized optimizers and quantized matrix operations that significantly reduce the memory footprint of training and inference workloads. By lowering the hardware requirements needed to work with large models, bitsandbytes helps make modern AI development more accessible to researchers and engineers. The library has become widely used in machine learning pipelines that rely on parameter-efficient training techniques and low-precision inference. -
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SageAttention
NeurIPS2025 Spotlight] Quantized Attention
...These optimizations allow models to perform matrix operations faster and consume less memory during inference. SageAttention is designed to function as a plug-and-play replacement for standard attention implementations, enabling developers to accelerate existing models without modifying their architecture. -
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MathPHP
Powerful modern math library for PHP
Math PHP is a library that brings advanced mathematical functions and data analysis capabilities to PHP applications. It covers a wide range of topics, including linear algebra, calculus, statistics, probability, and numerical analysis. Math PHP is designed for developers and data scientists who require precise and efficient mathematical computations in PHP, making it suitable for scientific computing and data processing. -
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tiny-llm
A course of learning LLM inference serving on Apple Silicon
tiny-llm is an educational open-source project designed to teach system engineers how large language model inference and serving systems work by building them from scratch. The project is structured as a guided course that walks developers through the process of implementing the core components required to run a modern language model, including attention mechanisms, token generation, and optimization techniques. Rather than relying on high-level machine learning frameworks, the codebase uses... -
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ITensors.jl
A Julia library for efficient tensor computations and tensor network
ITensors.jl is a high-performance Julia library for tensor network calculations, primarily used in quantum physics and computational science. It enables efficient manipulation of large, structured tensors with named indices and provides an intuitive interface for implementing algorithms like DMRG (Density Matrix Renormalization Group), TEBD (Time-Evolving Block Decimation), and more. ITensors.jl leverages Julia’s multiple dispatch and performance features to simplify the development of... -
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OpenGL Mathematics
Highly Optimized Graphics Math (glm) for C
Highly optimized 2D|3D math library, also known as OpenGL Mathematics (glm) for `C`. cglm provides lot of utils to help math operations to be fast and quick to write. It is community-friendly, feel free to bring any issues, bugs you faced. Almost all functions (inline versions) and parameters are documented inside the corresponding headers. OpenGL-related functions are dropped to make this lib platform/third-party independent. Make sure you have the latest version and feel free to report... -
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Tullio.jl
Tullio is a very flexible einsum macro
Tullio is a very flexible einsum macro. It understands many array operations written in index notation -- not just matrix multiplication and permutations, but also convolutions, stencils, scatter/gather, and broadcasting. Used by itself the macro writes ordinary nested loops much like Einsum.@einsum. One difference is that it can parse more expressions, and infer ranges for their indices. Another is that it will use multi-threading (via Threads. -
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Slambook2
edition 2 of the slambook
...Chapter folders let readers study individual techniques before connecting them into broader localization and mapping pipelines. Supplemental files include errata, exercise solutions, notes, figures, and small demonstrations of matrix and coordinate operations. It is intended for hands-on study and provides a clearer upgrade path than the original edition. -
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mathjs
An extensive math library for JavaScript and Node.js
mathjs is a comprehensive mathematics library for JavaScript and Node.js that provides advanced numerical, symbolic, and matrix computation capabilities through a flexible expression-based interface. The library supports a wide range of mathematical operations including algebra, statistics, complex numbers, fractions, units, matrices, and symbolic manipulation while maintaining compatibility across browsers and server environments. One of its defining features is its expression parser, which allows users to evaluate and manipulate mathematical expressions written in a natural math-like syntax. mathjs is highly modular, enabling developers to include only the functionality they need for optimized application size and performance. ... -
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frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
Use Keras models in C++ with ease. A lightweight header-only library for using Keras (TensorFlow) models in C++. Works out-of-the-box also when compiled into a 32-bit executable. (Of course, 64 bit is fine too.) Avoids temporarily allocating (potentially large chunks of) additional RAM during convolutions (by not materializing the im2col input matrix). Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can... -
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Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
...It provides a high-performance framework for numerical computing and machine learning within modern JavaScript runtimes. Built on Bun and Flashlight, with ArrayFire as its numerical backend, Shumai brings GPU-accelerated tensor operations, automatic differentiation, and scientific computing tools directly to JavaScript developers. It allows seamless integration of machine learning, deep learning, and custom differentiable programs into web-based or server-side environments without relying on Python frameworks. The library supports matrix operations, gradient computation, and tensor conversions with intuitive APIs and near-native speed, thanks to Bun’s low-overhead FFI bindings. ... -
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librsb
A shared memory parallel sparse matrix library including Sparse BLAS.
librsb is a library for sparse matrix computations featuring the Recursive Sparse Blocks (RSB) matrix format. This format allows cache efficient and multi-threaded (that is, shared memory parallel) operations on large sparse matrices. The most common operations necessary to iterative solvers are available, e.g.: matrix-vector multiplication, triangular solution, rows/columns scaling, diagonal extraction / setting, blocks extraction, norm computation, formats conversion. ... -
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A streamlined, directly compilable port of clSPARSE with a focus on simplicity and broad OpenCL device support. This project, maintained by Prof. Jinchuan Tang (jctang@gzu.edu.cn), is a derivative of the original clSPARSE library. Its primary goal is to eliminate the complexities of the original build system, offering a straightforward "clone and compile" experience. The library supports any OpenCL 1.2+ capable device and is designed for users who need sparse linear algebra operations...
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zkcm
A C++ library for multiprecision complex-number matrix calculations.
zkcm library is a C++ library for multi-precision complex-number matrix calculations. It provides a number of functionalities including the LU decomposition, the singular value decomposition, tensor product calculation, tracing-out operations, etc. -
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NumeRe
Framework for numerical computations, data analysis and visualisation
Curve fitting | Data analysis | Plotting | Matrix operations | FFT | Extensible framework | Multiple file formats | Programmable | Open source | Free for everyone NumeRe: Framework for Numerical Computation is a numerical framework written for Microsoft Windows(R) and released under the GNU GPL v3 for solving and visualizing mathematical and physical problems numerically. -
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Photon
A graphing calculator that's both powerful and easy to use.
Photon is a fully functional graphing calculator capable of numeric calculations as well as graphing functions, including parametric and polar graphs. In addition to regular graphing, Photon can plot integrals, first and second derivatives, tracing, animation, matrix math, and degree / radian mode. Photon can find roots, minimums and maximums, points of inflection, and it can fit several types of best fit lines and curves to data sets. Log and semi-log graphing are also...
