Sparse Computation Acceleration

Sparse Computation Acceleration is a coarse-grained reconfigurable architecture technique that exploits computational sparsity by selectively activating processing elements and bypassing zero-valued or pruned data operations to improve energy efficiency and throughput in sparse workloads.

227

Publications

17.1K

Citations

760

Authors

193

Institutions

Publications per year

2017–2026

129

Authors

760

  1. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    9 publications · 303 citations

    9

    h-index

  2. WJ
    William J. Dally

    Stanford University, United States

    8 publications · 4.9K citations

    8

    h-index

  3. JE
    Joel Emer

    Massachusetts Institute of Technology, United States

    8 publications · 1.9K citations

    8

    h-index

  4. YX
    Yuan Xie

    Pennsylvania State University, United States

    6 publications · 208 citations

    6

    h-index

  5. MH
    Mary Hall

    University of Utah, United States

    6 publications · 272 citations

    6

    h-index

1–5 of 760

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 1.8K citations

    11

    h-index

  2. 7

    h-index

  3. ACM Transactions on Mathematical Software

    TOMS · 5 publications · 364 citations

    5

    h-index

  4. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 5 publications · 221 citations

    5

    h-index

  5. 4

    h-index

1–5