Partitioning and Communication Strategies for Sparse Non-negative Matrix Factorization

Author:

Kaya Oguz1,Kannan Ramakrishnan2,Ballard Grey3

Affiliation:

1. Inria Bordeaux, Talence, France

2. Oak Ridge National Laboratory, Oak Ridge, TN

3. Wake Forest University, Winston-Salem, NC

Funder

Grand Équipement National De Calcul Intensif

U.S. Department of Energy

National Science Foundation

Publisher

ACM

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Accelerated Constrained Sparse Tensor Factorization on Massively Parallel Architectures;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12

2. HARP: Hardware-Based Pseudo-Tiling for Sparse Matrix Multiplication Accelerator;56th Annual IEEE/ACM International Symposium on Microarchitecture;2023-10-28

3. Performance Implication of Tensor Irregularity and Optimization for Distributed Tensor Decomposition;ACM Transactions on Parallel Computing;2023-06-20

4. On Large-Scale Matrix-Matrix Multiplication On Compressed Structures;2021 IEEE International Conference on Big Data (Big Data);2021-12-15

5. BaPa: A Novel Approach of Improving Load Balance in Parallel Matrix Factorization for Recommender Systems;IEEE Transactions on Computers;2021-05-01

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