Search Results for "sparse matrices"
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Showing 33 open source projects for "sparse matrices"
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PartitionedArrays.jl
Vectors and sparse matrices partitioned into pieces
This package provides distributed (a.k.a. partitioned) vectors and sparse matrices in Julia. See the documentation for further details. -
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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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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:... -
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RedisGraph
A graph database as a Redis module
A high-performance graph database module for Redis that enables fast graph processing and analytics using a query engine based on Cypher. -
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BitMagic Library
Compressed bit-sets, sparse bit matrices and algorithms
BitMagic - C and C++ library implementing dynamic bitvectors and bit-set algorithms with several types of on-the-fly, adaptive compression. Designed for use in databases, search systems, data-mining algorithms, scientific projects. The core of the library is C++, but it provides C-compatibility wrappers and can be compiled without C++ runtime. Optimizations for Intel SSE2, SSE4.2 and AVX2. -
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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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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. ... -
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SLAM++
high-performance nonlinear least squares solver for graph problems
SLAM++ is a minimalist implementation of incremental nonlinear least squares, containing lighting fast implementation of linear algebra on sparse block matrices. It is aimed for use in 3D reconstruction or robotics. -
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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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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. -
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Universal Java Matrix Package
sparse and dense matrix, linear algebra, visualization, big data
...Multi-dimensional matrices as well as generic matrices with a specified object type are supported and very large matrices can be handled even when they do not fit into memory. -
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The library for utilization of Minimal Quadtree format for storing very large sparse matrices. Please see the paper referenced below for the description of a problem. Corresponding papers: Tree-based Space Efficient Formats for Storing the Structure of Sparse Matrices (I. Šimeček, D. Langr, P. Tvrdík), In Scalable Computing: Practice and Experience, volume 15, 2014. Space Efficient Formats for Structure of Sparse Matrices Based on Tree Structures (I. ...
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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. -
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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... -
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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. -
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The Meta Matrix Library is a modular designed collection of C libraries. It was developed to provide easy and consistent access to numerical linear algebra software for sparse and dense matrices.
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TifaMMy isn't the fastest Matrix Multiplication yet! A library for cache oblivious matrix operations using the space filling Peano curve. Aim is for BLAS / LAPACK functionality (but with an intuitive C++ API).
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Seldon is a C++ library for linear algebra. It provides vectors and matrices: full, sparse, triangular, hermitian, ... It includes interfaces to Blas, Lapack, Mumps, SuperLU and UmfPack. Seldon implements several solvers such as Gmres, BiCgSTAB, Qmr,
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Processor Enhanced Recursive Dynamics
Processor Enhanced Robust Core Solver for Recursive Multibody Dynamics
...Processors embed model detail into runtime algorithms, minimizing rediscovery operations. Spatial algebra organizes and simplifies recursive algorithms. Gaussian Elimination with Complete Pivoting converts constraint Jacobian matrices and equations into Row-Reduced Echelon Form and partitions variables into Dependent/Independent sets. The constrained equations of motion are effectively converted from DAE to ODE form, allowing simple robust sparse factor and solve algorithms. Processors enhance and maintain most aspects of runtime algorithm performance, insuring continuous robust and efficient solutions. ... -
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yaUFget
Yet Another Python Interface to the UF sparse matrix collection
The package yaUFget is yet another interface to the collection of sparse matrices at the University of Florida for Python. In contrast with the official Python interface it can be easily used as a package and can be imported to any place, obtains the updated index of matrices from the collection's web site and does not require MATLAB. The functionality of the MATLAB's interface UFget was preserved. -
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This is a modified version of the UMFPACK library for the factorization of sparse unsymmetric matrices. This version can be compiled with the OPENCL flag in order to enable the use of GPGPU for the frontal operations.
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MatLib is intended to be an easy-to-use rock-solid linear algebra library for easily performing multithreaded numerical computations from the C language, involving both dense and sparse matrices.
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The JSparse Matrix Package, developed by Philipp Geigenmüller during an internship at the prudsys AG in Chemnitz, Germany, is an extension of the well-known Java Matrix Package (JAMA) and allows the use of sparse matrices and related algorithms.
