Suchergebnisse - Sparse Matrix-Sparse Matrix Multiplication

  1. 1

    Vesper: A Versatile Sparse Linear Algebra Accelerator With Configurable Compute Patterns von Jin, Hanchen, Yue, Zichao, Zhao, Zhongyuan, Du, Yixiao, Deng, Chenhui, Srivastava, Nitish, Zhang, Zhiru

    ISSN: 0278-0070, 1937-4151
    Veröffentlicht: New York IEEE 01.05.2025
    “… In particular, four compute kernels in SLA are widely used, including sparse-matrix-dense-vector multiplication, sparse-matrix-dense-matrix multiplication, sparse-matrix-sparse-vector multiplication …”
    Volltext
    Journal Article
  2. 2

    Multithreaded sparse matrix-matrix multiplication for many-core and GPU architectures von Deveci, Mehmet, Trott, Christian, Rajamanickam, Sivasankaran

    ISSN: 0167-8191, 1872-7336
    Veröffentlicht: United States Elsevier B.V 01.10.2018
    Veröffentlicht in Parallel computing (01.10.2018)
    “… ://github.com/kokkos/kokkos-kernels. Sparse matrix-matrix multiplication is a key kernel that has applications in several domains such as scientific computing and graph analysis …”
    Volltext
    Journal Article
  3. 3

    I/O-Optimal Cache-Oblivious Sparse Matrix-Sparse Matrix Multiplication von Gleinig, Niels, Besta, Maciej, Hoefler, Torsten

    ISSN: 1530-2075
    Veröffentlicht: IEEE 01.05.2022
    “… s. We present a cache-oblivious sparse matrix-sparse matrix multiplication algorithm that uses a worst-case number of I/O s that matches a previously established lower bound for this problem (0 (N2/B.M) read-I/Os and 0 (N2/B …”
    Volltext
    Tagungsbericht
  4. 4

    Level-based Blocking for Sparse Matrices: Sparse Matrix-Power-Vector Multiplication von Alappat, Christie, Hager, Georg, Schenk, Olaf, Wellein, Gerhard

    ISSN: 1045-9219, 1558-2183
    Veröffentlicht: New York IEEE 01.02.2023
    “… The multiplication of a sparse matrix with a dense vector (SpMV) is a key component in many numerical schemes and its performance is known to be severely limited by main memory access …”
    Volltext
    Journal Article
  5. 5

    ALBBA: An efficient ALgebraic Bypass BFS Algorithm on long vector architectures von Niu, Yuyao, Casas, Marc

    ISSN: 0167-8191
    Veröffentlicht: Elsevier B.V 01.09.2025
    Veröffentlicht in Parallel computing (01.09.2025)
    “… In the algebraic BFS paradigm, each BFS iteration is expressed as a sparse matrix–vector multiplication, allowing BFS to be accelerated and analyzed through well-established linear algebra primitives …”
    Volltext
    Journal Article
  6. 6

    Sparse Matrix Sparse Vector Multiplication - A Novel Approach von Shah, Monika

    ISSN: 1530-2016
    Veröffentlicht: IEEE 01.09.2015
    “… Sparse Matrix Vector Multiplication (SpMV) is a well-known kernel for such computing applications in science and engineering world …”
    Volltext
    Tagungsbericht
  7. 7

    CGA: Accelerating BFS Through an Sparsity-Aware Adaptive Framework on Heterogeneous Platforms von Xu, Lei, Jia, Haipeng, Zhang, Yunquan

    ISSN: 1045-9219, 1558-2183
    Veröffentlicht: IEEE 01.01.2026
    “… Direction optimization determines whether to use Sparse Matrix-Sparse Vector Multiplication (SpMSpV …”
    Volltext
    Journal Article
  8. 8

    Optimizing partitioned CSR-based SpGEMM on the Sunway TaihuLight von Chen, Yuedan, Xiao, Guoqing, Yang, Wangdong

    ISSN: 0941-0643, 1433-3058
    Veröffentlicht: London Springer London 01.05.2020
    Veröffentlicht in Neural computing & applications (01.05.2020)
    “… General sparse matrix-sparse matrix (SpGEMM) multiplication is one of the basic kernels in a great many applications …”
    Volltext
    Journal Article
  9. 9

    A Work-Efficient Parallel Sparse Matrix-Sparse Vector Multiplication Algorithm von Azad, Ariful, Buluc, Aydin

    ISSN: 1530-2075, 1530-2075
    Veröffentlicht: United States IEEE 01.05.2017
    “… We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multiplication (SpMSpV …”
    Volltext
    Tagungsbericht Journal Article
  10. 10

    Improving Efficiency of Parallel Vertex-Centric Algorithms for Irregular Graphs von Ozdal, Muhammet Mustafa

    ISSN: 1045-9219, 1558-2183
    Veröffentlicht: New York IEEE 01.10.2019
    “… Propagation blocking (PB) idea was proposed recently to improve the parallel performance of PageRank and sparse matrix and vector multiplication operations …”
    Volltext
    Journal Article
  11. 11

    Efficient implementation of sparse matrix-sparse vector multiplication for large scale graph analytics von Serrano, Mauricio J.

    ISSN: 2643-1971
    Veröffentlicht: IEEE 01.09.2019
    “… We developed a parallel algorithm to improve the cache behavior and overall performance for multiplication of sparse matrices with sparse vectors (SpMSpV …”
    Volltext
    Tagungsbericht
  12. 12

    An Efficient Gustavson-based Sparse Matrix-matrix Multiplication Accelerator on Embedded FPGAs von Li, Shiqing, Huai, Shuo, Liu, Weichen

    ISSN: 0278-0070, 1937-4151
    Veröffentlicht: New York IEEE 01.12.2023
    “… Sparse-matrix sparse-matrix multiplication (SpMM) is an important kernel in multiple areas, e.g …”
    Volltext
    Journal Article
  13. 13

    FSMM: An Efficient Matrix Multiplication Accelerator Supporting Flexible Sparsity von Qiao, Yuxuan, Yang, Fan, Zhang, Yecheng, Xiong, Xiankui, Yao, Xiao, Yao, Haidong

    ISSN: 1558-2434
    Veröffentlicht: ACM 27.10.2024
    “… Sparse matrix multiplication is a critical operation in deep learning. However, matrix sparsity leads to irregular data flow, which would degrade the efficiency of matrix multiplication …”
    Volltext
    Tagungsbericht
  14. 14
  15. 15

    GAS: General-Purpose In-Memory-Computing Accelerator for Sparse Matrix Multiplication von Zhang, Xiaoyu, Li, Zerun, Liu, Rui, Chen, Xiaoming, Han, Yinhe

    ISSN: 0018-9340, 1557-9956
    Veröffentlicht: New York IEEE 01.06.2024
    Veröffentlicht in IEEE transactions on computers (01.06.2024)
    “… Sparse matrix multiplication is widely used in various practical applications. Different accelerators have been proposed to speed up sparse matrix-dense vector multiplication (SpMV …”
    Volltext
    Journal Article
  16. 16

    SpecBoost: Accelerating Tiled Sparse Matrix Multiplication via Dataflow Speculation von Seo, Gwanghwi, Ryu, Sungju

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: Piscataway IEEE 2025
    Veröffentlicht in IEEE access (2025)
    “… Sparse matrix-sparse matrix multiplication (SpMSpM) is crucial in many fields such as scientific computing, sparse linear algebra, and machine learning due to its computational complexity in the large and extremely sparse datasets …”
    Volltext
    Journal Article
  17. 17

    Performance Evaluation of Accurate Matrix-Matrix Multiplication on GPU Using Sparse Matrix Multiplications von Ishiguro, Fumiya, Katagiri, Takahiro, Ohshima, Satoshi, Nagai, Toru

    Veröffentlicht: IEEE 01.11.2020
    “… We contribute the following two points: (1) We evaluate the performance of sparse matrix - dense matrix multiplication (SpMM …”
    Volltext
    Tagungsbericht
  18. 18

    Performance-Aware Model for Sparse Matrix-Matrix Multiplication on the Sunway TaihuLight Supercomputer von Chen, Yuedan, Li, Kenli, Yang, Wangdong, Xiao, Guoqing, Xie, Xianghui, Li, Tao

    ISSN: 1045-9219, 1558-2183
    Veröffentlicht: New York IEEE 01.04.2019
    “… General sparse matrix-sparse matrix multiplication (SpGEMM) is one of the fundamental linear operations in a wide variety of scientific applications …”
    Volltext
    Journal Article
  19. 19

    A work-efficient parallel sparse matrix-sparse vector multiplication algorithm von Azad, Ariful, Aydin Buluc

    ISSN: 2331-8422
    Veröffentlicht: Ithaca Cornell University Library, arXiv.org 25.10.2016
    Veröffentlicht in arXiv.org (25.10.2016)
    “… We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multiplication (SpMSpV …”
    Volltext
    Paper
  20. 20

    Level-based Blocking for Sparse Matrices: Sparse Matrix-Power-Vector Multiplication von Alappat, Christie L, Hager, Georg, Schenk, Olaf, Wellein, Gerhard

    ISSN: 2331-8422
    Veröffentlicht: Ithaca Cornell University Library, arXiv.org 03.05.2022
    Veröffentlicht in arXiv.org (03.05.2022)
    “… The multiplication of a sparse matrix with a dense vector (SpMV) is a key component in many numerical schemes and its performance is known to be severely limited by main memory access …”
    Volltext
    Paper