Anil Gaihre

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 10

Top Topics

Tensor Decomposition

Proximity Search

Highly Scalable

Top Venues

Publications

Shilong Wang, Hang Liu, Anil Gaihre, Hengyong Yu
ezLDA: Efficient and Scalable LDA on GPUs. IEEE Access 11 (2023)
Andy Trinh, Shivam Sheth, Anil Gaihre, Caiwen Ding, Jieyang Chen, Feiyi Wang, David Pugmire, Scott Klasky, Hang Liu, Lipeng Wan
Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics. HPCC/DSS/SmartCity/DependSys (2023)
Anil Gaihre, Xiaoye Sherry Li, Hang Liu
gSoFa: Scalable Sparse Symbolic LU Factorization on GPUs. IEEE Trans. Parallel Distributed Syst. 33 (4) (2022)
Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu
Dr. Top-k: Delegate-Centric Top-k on GPUs. CoRR (2021)
Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu
Dr. Top-k: delegate-centric Top-k on GPUs. SC (2021)
Anil Gaihre, Xiaoye S. Li, Hang Liu
GSoFa: Scalable Sparse LU Symbolic Factorization on GPUs. CoRR (2020)
Shilong Wang, Hang Liu, Anil Gaihre, Hengyong Yu
EZLDA: Efficient and Scalable LDA on GPUs. CoRR (2020)
Anil Gaihre, Zhenlin Wu, Fan Yao, Hang Liu
XBFS: eXploring Runtime Optimizations for Breadth-First Search on GPUs. HPDC (2019)
Anil Gaihre, Santosh Pandey, Hang Liu
Deanonymizing Cryptocurrency With Graph Learning: The Promises and Challenges. CNS (2019)
Anil Gaihre, Yan Luo, Hang Liu
Do Bitcoin Users Really Care About Anonymity? An Analysis of the Bitcoin Transaction Graph. IEEE BigData (2018)