Search Results for "blas"
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Showing 48 open source projects for "blas"
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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. -
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Peroxide
Rust numeric library with high performance and friendly syntax
Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. For users familiar with numerical computing libraries like NumPy, MATLAB, or R, Rust's syntax might seem unfamiliar at first. This can make it more challenging to learn and use Rust libraries that heavily rely on Rust's unique features and syntax. -
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AppleAccelerate.jl
Julia interface to the macOS Accelerate framework
Julia interface to the macOS Accelerate framework. This provides a Julia interface to some of the macOS Accelerate frameworks. At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced accuracy. -
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OpenBLAS
OpenBLAS is an optimized BLAS library based on GotoBLAS2.
OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version. -
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Kimi K3 in C
A 2.78-trillion-parameter Kimi K3 running inference on a single CPU
Kimi K3 in C is a portable C99 inference engine built to run the 2.78-trillion-parameter Kimi K3 model on CPUs without BLAS, machine-learning frameworks, or GPUs. It demonstrates inference from a roughly 1.56 TB checkpoint with measured memory use as low as 8.24 GB. The runtime streams model trunk layers and routed experts from disk instead of keeping all weights resident in memory. Memory presets balance pinned layers and an expert LRU cache for laptops, desktops, workstations, and servers. ... -
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Colibrì
Run GLM-5.2 (744B MoE) on a 25GB-RAM consumer machine
...It keeps the dense portion of the quantized model in memory while streaming routed experts from a large disk-based store as they are needed. The runtime is implemented in pure C, requires no Python or BLAS during inference, and can operate without a GPU. Compressed attention caches, expert caching, optional hot tiers, and speculative decoding reduce memory pressure and improve repeated use. A planning tool calculates safe disk, RAM, and VRAM placement before loading the model, while a diagnostic command checks system readiness. Colibri includes terminal chat, an OpenAI-compatible text API, and a browser client, but disk-bound generation can be slow on cold caches. -
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LinearSolve.jl
High-Performance Unified Interface for Linear Solvers in Julia
LinearSolve.jl is a unified interface for the linear solving packages of Julia. It interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code. Performance is key: the current methods are made to be highly performant on scalar and statically sized small problems,... -
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Faiss
Library for efficient similarity search and clustering dense vectors
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It... -
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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.
...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. librsb implements the Sparse BLAS standard, as specified in the BLAS Forum documents. -
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ceenv
Computer Experiment Environment
...It is being developed and distributed as a training environment of UNIX (UNIX commands, network, Emacs, Gnuplot), programming language (C, C++, Fortran, Python 2/3, MPI, OpenMP, BLAS/LAPACK), etc. The whole environment is included in one VirtualBox virtual disk image, and users can use it immediately by simply importing the image into VirtualBox. -
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octave-ocl
OpenCL support for GNU Octave
...The Package offers new numeric data types with many built-in operations (e.g., overloaded operators). It is flexibly extendible by user-written OpenCL C programs. The Package does not, by itself, provide parallelization of higher numerical methods (like BLAS or LAPACK). The Package is also available from the corresponding Octave Forge webpage https://octave.sourceforge.io/ocl/index.html. More information on GNU Octave can be found at https://www.octave.org. -
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Gaius.jl
Divide and Conquer Linear Algebra
Gaius.jl is a multi-threaded BLAS-like library using a divide-and-conquer strategy to parallelism, and built on top of the fantastic LoopVectorization.jl. Gaius spawns threads using Julia's depth-first parallel task runtime and so Gaius's routines may be fearlessly nested inside multi-threaded Julia programs. Gaius is not stable or well-tested. Only use it if you're adventurous. -
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C++ Math Expression Parser
C++ Math Expression Parser Library
The C++ Mathematical Expression Toolkit Library (ExprTk) is a simple to use, easy to integrate and extremely efficient run-time mathematical expression parser and evaluation engine. ExprTk supports numerous forms of functional, logical and vector processing semantics and is very easily extendible. Download http://partow.net/programming/exprtk/index.html -
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ATLAS (Automatically Tuned Linear Algebra Software) provides highly optimized Linear Algebra kernels for arbitrary cache-based architectures. ATLAS provides ANSI C and Fortran77 interfaces for the entire BLAS API, and a small portion of the LAPACK AP
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The Ada 2005 standard defines real and complex matrix and vector operations. Not every possible operation is supported, so for example only symmetric or hermitian matrices can be solved. This project provides extensions to the Standard for GNAT. The software is issued under the GPL Version 3 with the GCC Runtime Library Exception.
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Grenade
Deep Learning in Haskell
Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only... -
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MatLisp is a package for Common Lisp for handling matrices with real-valued or complex-valued elements. BLAS is used for elementary matrix operations and LAPACK is used for linear algebra routines.
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This package provides many state-of-the-art algorithms to optimize a smooth cost function defined on a Riemannian manifold. The package is written in C++ and uses the standard linear algebra libraries: BLAS and LAPACK. It can be used alone in a C++ environment or in Matlab with a Mex interface. The package is more reliable and requires smaller computational time compared with code written only in Matlab. Users need only provide a cost function, gradient function, and the action of the Riemannian Hessian (if a Newton method is used) in Matlab or C++. ...
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CPPLapack is a c++ class wrapper for BLAS, LAPACK and PARDISO. Its special features are the followings. [1]User-friendly interface [2]Hi-speed matrix calculations using BLAS and LAPACK [3]Minimized number of copy times using Smart Temporary system
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Template Matrix/Vector Library for C++
A fast, intuitive linear algebra library for C++.
TMV is a comprehensive linear algebra library which uses operator overloading, views & delayed evaluation to simplify matrix and vector expressions in C++. It is well documented and can optionally call optimized BLAS/LAPACK for faster execution times -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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OmpBLAS
Implementation of BLAS specification using OpenMP
This C implementation of one of the most used algebra libraries in scientific applications makes use of OpenMP to take advantage of modern multithread CPUs, while it still keeps in mind the underlying idea in the BLAS specification which allow cache-friendly code. -
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Fluid2D
Fluid2D is the Swiss army knife of 2D CFD
...Its numerics has been chosen to yield to as small dissipation as possible allowing to simulate easily high Reynolds flows, much higher than any of its concurrents. High performances are achieved by writting most of the operations as matrix-vector multiplications, handled by numpy that itself relies on the highly optimized BLAS. -
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CVM C++ Class Library encapsulates concepts of vector and square, band, symmetric and hermitian matrices in Euclidean space of real and complex numbers. It utilizes BLAS and LAPACK Fortran libraries. See http://cvmlib.com for binaries and more details.