Gpu Runtime Systems

GPU Runtime Systems is a specialized runtime system that manages the execution of parallel tasks on graphics processing units, distinguished by its support for massive thread-level parallelism, hierarchical memory management, and hardware-specific optimizations tailored to GPU architectures.

364

Publications

17.3K

Citations

1.2K

Authors

345

Institutions

Publications per year

2017–2026

119

Authors

1.2K

  1. XS
    Xipeng Shen

    North Carolina State University, United States

    10 publications · 585 citations

    10

    h-index

  2. SK
    Shinpei Kato

    The University of Tokyo, Japan

    9 publications · 686 citations

    9

    h-index

  3. RR
    Ragunathan Rajkumar

    Carnegie Mellon University, United States

    7 publications · 500 citations

    7

    h-index

  4. BH
    Bingsheng He

    National University of Singapore, Singapore

    6 publications · 730 citations

    6

    h-index

  5. DK
    David Kaeli

    Northeastern University, United States

    5 publications · 225 citations

    5

    h-index

1–5 of 1.2K

Venues

  1. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 11 publications · 835 citations

    11

    h-index

  2. ACM SIGPLAN Notices

    9 publications · 298 citations

    9

    h-index

  3. Parallel Computing

    8 publications · 1.1K citations

    8

    h-index

  4. The Journal of Supercomputing

    6 publications · 105 citations

    6

    h-index

  5. ACM Transactions on Architecture and Code Optimization

    TACO · 6 publications · 128 citations

    6

    h-index

1–5