• LAPACK

  • Referenced in 1702 articles [sw00503]
  • banded matrices are handled, but not general sparse matrices. In all areas, similar functionality ... LINPACK libraries run efficiently on shared-memory vector and parallel processors. On these machines, LINPACK ... algorithms to use block matrix operations, such as matrix multiplication, in the innermost loops. These...
  • INTLAB

  • Referenced in 471 articles [sw04004]
  • real and complex sparse matrices (very fast) automatic differentiation (forward mode, vectorized computations, fast) Gradients ... product and matrix-vector residuals (interpreted, reference implementation, slow) multiple precision interval arithmetic with error...
  • Sparsity

  • Referenced in 13 articles [sw08686]
  • Framework for Sparse Matrix Kernels. Sparse matrixvector multiplication is an important computational kernel that ... allowing users to automatically build sparse matrix kernels that are tuned to their matrices ... operations: a sparse matrix times a dense vector and a sparse matrix times ... optimizations are important when the vector used in multiplication is larger than the cache size...
  • SELL_C_sigma

  • Referenced in 11 articles [sw11232]
  • data format for efficient general sparse matrix-vector multiplication on modern processors with wide SIMD ... units. Sparse matrix-vector multiplication (spMVM) is the most time-consuming kernel in many numerical ... accelerator architectures. However, the optimal sparse matrix data storage format is highly hardware-specific, which ... unclear how the wide single instruction multiple data (SIMD) units in current multi- and many...
  • LSRN

  • Referenced in 27 articles [sw09555]
  • matrix and matrix-vector multiplications, it can be a dense or sparse matrix...
  • clSpMV

  • Referenced in 10 articles [sw12638]
  • OpenCL SpMV framework on GPUs. Sparse matrix vector multiplication (SpMV) kernel is a key computation ... efforts to optimize the SpMV kernel in sparse linear algebra. With the appearance of OpenCL ... this paper, we propose a new sparse matrix format, the Cocktail Format, to take advantage...
  • Aztec

  • Referenced in 84 articles [sw12817]
  • iterative solvers, preconditioners and matrix-vector multiplication routines. Users are not required to provide their ... necessary transformations for the matrix-vector multiplication and preconditioning. After the transformations, the iterative solvers ... sparse LU, ILU, ILUT, BILU and ICC within domains). Aztec supports two different sparse matrix ... library includes highly optimized matrix-vector multiply kernels and preconditioners for both types of data...
  • DVDSON

  • Referenced in 16 articles [sw17845]
  • extreme eigenpairs of a large, sparse, real, symmetric matrix A program is presented for determining ... spectrum of a large, real, symmetric matrix. Based on the Davidson method, which is extensively ... algorithm by adopting several extensions. The matrix-vector multiplication routine that it requires ... efficient sparse matrix representation and a matrix-vector multiplication are given. Some comparisons with...
  • FE-gMG

  • Referenced in 8 articles [sw10365]
  • technique based on cascades of sparse matrix-vector multiplication by applying strong smoothers. In particular...
  • CSR5

  • Referenced in 3 articles [sw23688]
  • Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication. Sparse matrix-vector multiplication (SpMV ... this paper, we propose CSR5 (Compressed Sparse Row 5), a new storage format, which offers ... sparsity structure of the input matrix. Thus the single format can support an SpMV algorithm...
  • TAUCS

  • Referenced in 32 articles [sw04014]
  • file systems. Out-of-Core Sparse LU with Partial Pivoting Factor and Solve. Can solve ... vector multiplication, triangular solvers, matrix reordering. Matrix Input/Output. Routines to read and write sparse matrices...
  • LightSpMV

  • Referenced in 2 articles [sw23689]
  • LightSpMV: Faster CSR-based sparse matrix-vector multiplication on CUDA-enabled GPUs. Compressed sparse ... sparse matrix storage. However, the state-of-the-art CSR-based sparse matrix-vector multiplication ... from the fine-grained dynamic distribution of matrix rows over warps/vectors. In LightSpMV, two dynamic ... distribution approaches have been investigated at the vector and warp levels with atomic operations...
  • AdELL

  • Referenced in 1 article [sw23692]
  • Balancing ELL Format for Efficient Sparse Matrix-Vector Multiplication on GPUs. The sparse matrix-vector ... paper, we propose a novel ELL-based matrix format called Adaptive ELL (AdELL) to improve ... warps) that take full advantage of the vectorized execution on Streaming Multiprocessors (SMs). The AdELL ... operations to distribute very skewed rows over multiple warps. Moreover, we introduce a loop unrolling...
  • SparseX

  • Referenced in 1 article [sw25566]
  • library for high-performance sparse matrix-vector multiplication on multicore platforms. The Sparse Matrix-Vector ... many iterative methods for the solution of sparse linear systems, and often constitutes a severe ... data structures used to store the sparse matrix, has always been of particular interest...
  • tpSpMV

  • Referenced in 1 article [sw38268]
  • phase large-scale sparse matrix-vector multiplication kernel for manycore architectures. Sparse matrix-vector multiplication ... multicore and manycore architectures based on Compressed Sparse Row (CSR) format via row-wise parallelization...
  • CoAdELL

  • Referenced in 1 article [sw23691]
  • Adaptivity and Compression for Improving Sparse Matrix-Vector Multiplication on GPUs. Numerous applications in science ... fundamental kernel such as the Sparse Matrix-Vector multiplication (SpMV) is crucial for solving increasingly ... adaptivity and compression into an ELL-based sparse format in order to improve the state ... work is AdELL, an efficient sparse data structure based on the idea of distributing working...
  • GraphR

  • Referenced in 1 article [sw35259]
  • algorithm can be expressed in sparse matrix vector multiplication (SpMV), it can be efficiently performed ... core graph computations are performed in sparse matrix format in GEs (ReRAM crossbars). The vector/matrix-based...
  • pOSKI

  • Referenced in 1 article [sw30963]
  • sparse matrices, such as Sparse-Matrix-Vector-Multiplication (SpMV). pOSKI targets both uniprocessor and multicore ... attain high performance in commonly used sparse matrix operations, via autotuning...
  • SMATER

  • Referenced in 1 article [sw30962]
  • multicore and many-core architecture. Sparse matrix vector multiplication (SpMV) is an important computational kernel ... interface based on the compressed sparse row (CSR) sparse matrix format by implicitly choosing...
  • SpMV

  • Referenced in 1 article [sw41804]
  • multicore and many-core architecture. Sparse matrix vector multiplication (SpMV) is an important computational kernel ... interface based on the compressed sparse row (CSR) sparse matrix format by implicitly choosing...