Search Results for "sparse matrix"
Sort By:
Showing 40 open source projects for "sparse matrix"
View related business solutions-
Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
-
1
SuiteSparse
The official SuiteSparse library: a suite of sparse matrix algorithms
The official SuiteSparse library: a suite of sparse matrix algorithms authored or co-authored by Tim Davis, Texas A&M University. -
2
LRSLibrary
Low-Rank and Sparse Tools for Background Modeling and Subtraction
...The algorithms can also be adapted to other computer vision or machine learning problems beyond video. Large algorithm collection: > 100 matrix- and tensor-based low-rank + sparse methods. Open-source license, documentation and references included. -
3
CasADi
CasADi is a symbolic framework for numeric optimization
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. ... -
4
libCEED
CEED Library: Code for Efficient Extensible Discretizations
...While our focus is on high-order finite elements, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the user manual and API implementation portion of the documentation. One of the challenges with high-order methods is that a global sparse matrix is no longer a good representation of a high-order linear operator, both with respect to the FLOPs needed for its evaluation, as well as the memory transfer needed for a matvec. Thus, high-order methods require a new "format" that still represents a linear (or more generally non-linear) operator, but not through a sparse matrix. -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
5
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. ... -
6
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...
-
7
Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
8
Rotations.jl
Julia implementations for different rotation parameterizations
...This package implements various 3D rotation parameterizations and defines conversions between them. 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. -
9
falkordb
A super fast Graph Database
A super fast Graph Database uses GraphBLAS under the hood for its sparse adjacency matrix graph representation. Our goal is to provide the best Knowledge Graph for LLM (GraphRAG). -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
10
MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
-
11
DiffEqOperators.jl
Linear operators for discretizations of differential equations
...Care is taken to give efficiency by avoiding unnecessary allocations, using purpose-built stencil compilers, allowing GPUs and parallelism, etc. Any operator can be concretized as an Array, a BandedMatrix or a sparse matrix. -
12
Tensor Algebra Compiler
The Tensor Algebra Compiler (taco) computes sparse tensor expressions
A fast and versatile compiler-based library for sparse linear and tensor algebra. TACO can be used to implement sparse linear and tensor algebra applications in a wide range of domains. TACO supports a wide range of sparse (and dense) linear/tensor algebra computations, from simpler ones like sparse matrix-vector multiplication to more complex ones like MTTKRP on higher-order sparse tensors. -
13
A symbolic framework for C++, Python and Octave implementing automatic differentiation by source code transformation in forward and reverse modes on sparse matrix-valued computational graphs.
-
14
BlockSparse
Efficient GPU kernels for block-sparse matrix multiplication
The blocksparse repository provides efficient GPU kernels (TensorFlow custom ops) for block-sparse matrix multiplication and convolution operations. The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse patterns to scale better. ... -
15
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. -
16
LightSpMV
lightweight GPU-based sparse matrix-vector multiplication (SpMV)
LightSpMV is a novel CUDA-compatible sparse matrix-vector multiplication (SpMv) algorithm using the standard compressed sparse row (CSR) storage format. We have evaluated LightSpMV using various sparse matrices and further compared it to the CSR-based SpMV subprograms in the state-of-the-art CUSP and cuSPARSE. Performance evaluation reveals that on a single Tesla K40c GPU, LightSpMV is superior to both CUSP and cuSPARSE, with a speedup of up to 2.60 and 2.63 over CUSP, and up to 1.93 and 1.79 over cuSPARSE for single and double precision, respectively. -
17
Universal Java Matrix Package
sparse and dense matrix, linear algebra, visualization, big data
The Universal Java Matrix Package (UJMP) is an open source Java library which provides sparse and dense matrix classes, as well as a large number of calculations for linear algebra such as matrix multiplication or matrix inverse. Operations such as mean, correlation, standard deviation, replacement of missing values or the calculation of mutual information are supported, too. -
18
Fluid Gravity 3way
there are 3 observers to every curve, each seeing the other 2
I recently dug up some of my old simulations after to my surprise 3SAT and a theoretical expansion of boltzmann statistics reminded me I already simulated something like that but I didnt know how good a simulation it was. Check how the varying density and shape of electron clouds and soliton-like or fluid drop like blobs of field gradually start to point outward and get thinner, like a soliton is bell curve shaped as seen from outside. More importantly, compare the 2 halfs of electron cloud... -
19
ViennaCLBench
OpenCL linear algebra benchmark GUI for CPUs, GPUs, and MIC
ViennaCLBench provides a graphical user interface for collecting benchmark data for common OpenCL-accelerated linear algebra operations as implemented in the linear algebra library ViennaCL. -
20
Immutable Sparse Wave Trees (WaveTree)
Realtime bigdata tool for bit strings up to 2^63 based on AVL forest
...All those operations can be done millions of times per second regardless of size because the AVL forest reuses existing branches recursively. Theres a scalar (originally for copy/pasting subranges of sounds) and a bit Java package. Sparse n dimensional matrix. -
21
-
22
SL2
SL2 (= SLSL) - A Simple Linear Systems Library
SL2 is a C++ template library for solving systems of linear equations, providing the most common algorithms for dense and sparse systems. It uses OpenMP for parallelization and has no other dependencies. As the name suggests, SL2's implementation is staightforward with a focus on clear concepts, easy usage and understandable code. -
23
YAFEMS
Yet Another Finite Element Method Solver
YAFEMS (Yet Another Finite Element Method Solver) is a FEM solver for Linux and WIndows that reads a MED mesh file produced by Salome (http://www.salome-platform.org/) with certain groups created into the mesh, and with the help of an input text file (.yaf), performs a 3D or 2D plane stress or plane strain analysis and creates results in plain text format and in MED format. This way a complete analysis can be carried inside Salome, where a mesh file can be created, exported and read by... -
24
Colt provides a set of Open Source Libraries for High Performance Scientific and Technical Computing in Java http://acs.lbl.gov/~hoschek/colt/ This project starteda as a port of the Colt core library to C#, but contains additional features.
-
25
Block Matrix library
Highly efficient implementation of BLAS for sparse block matrices.
Highly efficient implementation of BLAS for sparse block matrices. Accelerated using heavy-duty C++ meta-programming, SIMD instructions and GPU.
