1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.IR2021
Dr. Top-k: Delegate-Centric Top-k on GPUs
Anil Gaihre, Da Zheng, Scott Weitze +5
Recent top- computation efforts explore the possibility of revising various sorting algorithms to answer top- queries on GPUs. These endeavors, unfortunately, perform signifi…
cs.DC2020
EZLDA: Efficient and Scalable LDA on GPUs
Shilong Wang, Hang Liu, Anil Gaihre +1
LDA is a statistical approach for topic modeling with a wide range of applications. However, there exist very few attempts to accelerate LDA on GPUs which come with exceptional com…
cs.DC2020★ 1 cited
GSoFa: Scalable Sparse Symbolic LU Factorization on GPUs
Anil Gaihre, Xiaoye S. Li, Hang Liu
Decomposing matrix A into a lower matrix L and an upper matrix U, which is also known as LU decomposition, is an essential operation in numerical linear algebra. For a sparse matri…