Search Results for "multiplication"
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Showing 109 open source projects for "multiplication"
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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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Rotations.jl
Julia implementations for different rotation parameterizations
...At their heart, each rotation parameterization is a 3×3 unitary (orthogonal) matrix (based on the StaticArrays.jl package), and acts to rotate a 3-vector about the origin through matrix-vector multiplication. While the RotMatrix type is a dense representation of a 3×3 matrix, we also have sparse (or computed, rather) representations such as quaternions, angle-axis parameterizations, and Euler angles. All rotation types support one(R) to construct the identity rotation for the desired parameterization. -
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NNlib.jl
Neural Network primitives with multiple backends
This package provides a library of functions useful for neural networks, such as softmax, sigmoid, batched multiplication, convolutions and pooling. Many of these are used by Flux.jl, which loads this package, but they may be used independently. -
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Book1_Python-For-Beginners
The Iris Book: Addition, Subtraction, Multiplication, and Division
Book1_Python-For-Beginners is the introductory volume of the Visualize-ML series, designed to teach Python programming to newcomers with no prior coding experience. The repository emphasizes clarity and gradual skill building, starting from fundamental syntax and moving toward practical programming patterns. It integrates visual aids and annotated code examples to help learners understand not just how Python works but why certain patterns are used. The material is structured to support... -
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Book3_Elements-of-Mathematics
From Addition, Subtraction, Multiplication, and Division to ML
Book3_Elements-of-Mathematics is an open learning resource in the Visualize-ML collection that introduces core mathematical foundations required for modern data science and AI. The repository presents topics such as algebra, calculus fundamentals, and mathematical reasoning using a highly visual and beginner-friendly approach. Its goal is to reduce the intimidation barrier often associated with formal mathematics by combining diagrams, structured explanations, and applied examples. The... -
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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.@spawn) and recursive tiling, on large enough arrays. -
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Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
Shumai is an experimental differentiable tensor library for TypeScript and JavaScript, developed by Facebook Research. 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... -
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Book6_First-Course-in-Data-Science
From Addition, Subtraction, Multiplication, and Division to ML
Book6_First-Course-in-Data-Science is an open-source educational project that serves as part of the “Iris Book” series focused on teaching data science and machine learning concepts through a combination of mathematics, programming, and visualization. The repository contains draft chapters, supporting Python code, and visual materials designed to guide readers from basic mathematical operations toward practical machine learning understanding. The goal of the project is to make complex topics... -
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CUTLASS
CUDA Templates for Linear Algebra Subroutines
CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN. CUTLASS decomposes these "moving parts" into reusable, modular software components abstracted by C++ template classes. These thread-wide, warp-wide, block-wide, and device-wide primitives can be specialized and tuned via custom tiling sizes, data types, and other algorithmic policy. ... -
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Clash
Haskell to VHDL/Verilog/SystemVerilog compiler
Clash is a functional hardware description language that borrows both its syntax and semantics from the functional programming language Haskell. It provides a familiar structural design approach to both combinational and synchronous sequential circuits. The Clash compiler transforms these high-level descriptions to low-level synthesizable VHDL, Verilog, or SystemVerilog. Clash is an open-source project, licensed under the permissive BSD2 license, and actively maintained by QBayLogic. The... -
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tt-metal
TT-NN operator library, and TT-Metalium low level kernel programming
tt-metal, also referred to in its documentation as TT-Metalium, is Tenstorrent’s low-level software development kit for programming applications on Tenstorrent AI accelerators. The project is designed for developers who need direct access to the company’s Tensix processor architecture, exposing a programming model that is closer to hardware control than high-level inference frameworks. Instead of following a traditional GPU model centered on massive thread parallelism, the platform is built... -
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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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decimal
Arbitrary-precision fixed-point decimal numbers in go
...Note: Decimal library can "only" represent numbers with a maximum of 2^31 digits after the decimal point. The zero-value is 0, and is safe to use without initialization. Addition, subtraction, and multiplication with no loss of precision. Division with specified precision. Database/sql serialization/deserialization. JSON and XML serialization/deserialization. big.Int's API is built to reduce the number of memory allocations for maximal performance. This makes sense for its use-case, but the trade-off is that the API is awkward and easy to misuse. ... -
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Hypercomplex Algebra Toolkit (HAT)
A Matlab code toolkit for arbitrary hypercomplex algebras
A flexible toolkit using Matlab's object-oriented features to provide user-configurable support for multiple hypercomplex algebras, essentially by defining the multiplication table. Using a two-level hierarchy of classes, a large body of code is made universal across algebras (for example, the code for multiplication, and addition). Matlab itself implements array indexing, colon notation etc. -
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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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librsb
A shared memory parallel sparse matrix library including Sparse BLAS.
...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. The RSB format is especially well suited for symmetric and transposed multiplication variants. On these variants, librsb has been found to be faster than Intel MKL's implementation for CSR. Most numerical kernels code is auto generated, and the supported numerical types can be chosen by the user at build time. ... -
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AQL
Advanced Query Language
.../ Logical regular expression matches /- Split string by regular expression /+ Replace by regular expression // All matches = Assignment + Addition or concatenation - Subtraction / Division * Multiplication -
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coral-ctc-terminal-calculator
A minimal calculator application for terminal lovers
CTC is a minimal and easy-to-use calculator application for your terminal. This project is meant for people who are quick with terminal applications, who may want a replacement for a GUI calculator. -
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QxCalc
QxCalc, a scriptable calculator
QxCalc For mathematical calculations in high-school, physics, chemistry, mathematics, economics, electrical, mechanical. Create equations, and also calculate with them, with ease. You use the calculator the same way as you use a pen and paper. It is quite simple, and can do a lot of work given syntax correctness. It comes with a "basic" gui, however the best way to use it is with the 'vim' editor, for which it has a syntax highlight file (calc.vim). -
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Elite Calculator
Elite Calculator - Accurate Math Solutions
...Designed with a sleek interface and packed with features, it's your all-in-one math assistant. Key Features: 🔢 Standard Calculator: Perform basic arithmetic operations like addition, subtraction, multiplication, and division. 📐 Scientific Mode: Access advanced functions for trigonometry, logarithms, and more. 🎨 Customizable Themes: Switch between light and dark themes. 📏 Dynamic Font Adjustment: Ensures clear and readable calculations. 🌐 Offline: No data collection, no ads. ⌨️ Keyboard Shortcuts: Enhance productivity. ... -
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matgts
programs for geotechnical engineering and mathematics
...mtfem - finite element analysis, 2D, plane strain state (C, SDL), GNU/Linux and Wind0ws executables present; mtpile - analysis of a laterally loaded pile (C, SDL); mtslope - slope stability and displacement analysis using limit equilibrium (C,SDL); jswall - analysis of a diaphragm wall (JavaScript); jsmath - mathematics: polynomial equations, linear systems of equations, eigenvalues, matrix multiplication, matrix inversion (JavaScript); mtwall - obsolete program for analysing a diaphragm wall (C, SDL). Some Javascript programs require at least Firefox 3 or 4, because of <canvas> and "use strict". -
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QwikTape
Do calculations, annotate it like you would on a paper "qwikly".
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Java Calculator
Supports PEDMAS order of computation and Reverse Polish Notation Gener
...Performs the computation of the arithmetic expression if Integers or Floating point numbers are used in the expression. Supports PEDMAS order of computation, thus, all the operators of Exponentiation, Division, Multiplication, Addition and Subtraction, as well as using Parentheses for grouping and prioritization is all handled. -
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AlphaTensor
AI discovers faster, efficient algorithms for matrix multiplication
AlphaTensor, developed by Google DeepMind, is the research codebase accompanying the 2022 Nature publication “Discovering faster matrix multiplication algorithms with reinforcement learning.” The project demonstrates how reinforcement learning can be used to automatically discover efficient algorithms for matrix multiplication — a fundamental operation in computer science and numerical computation. The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. ... -
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simple calculator ->>> typing string-> converting string to two arraylists (one with numbers second with operators)-> searching from left for privileged operators-> calculating them-> returning result as a string. //---REQUIRES JAVA JDK---//
