Search Results for "sparse matrices"
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12 projects for "sparse matrices" with 2 filters applied:
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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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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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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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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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The Lidy project is a small cross-platform library under LPGL licence, written in C language. It has been designed in order to facilitate the sparse matrices handling.
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I/O routines and tools for sparse matrices.
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uBLAS is a C++ template class library that provides BLAS level 1, 2, 3 functionality for dense, packed and sparse matrices and many numerical algorithms for linear algebra.
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Sparse is a direct method solver for the large sparse matrices that are associated with electrical circuit simulation. It uses LU factorization and handles both real and complex square matrices.It is intended to solve many matrices with the same structure
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MatGen is a matrix generator. It outputs matrices in MatrixMarket file format, taking as input a file describing the matrices´ properties. Currently it supports only random sparse matrices.
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