Distributed-memory parallel algorithms for sparse times tall-skinny-dense matrix multiplication

Author:

Selvitopi Oguz1,Brock Benjamin2,Nisa Israt1,Tripathy Alok2,Yelick Katherine2,Buluç Aydın1

Affiliation:

1. Lawrence Berkeley National Laboratory

2. University of California, Berkeley

Funder

Exascale Computing Project

National Science Foundation

Advanced Scientific Computing Research

Publisher

ACM

Cited by 12 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. Sparsity-Aware Communication for Distributed Graph Neural Network Training;Proceedings of the 53rd International Conference on Parallel Processing;2024-08-12

2. Two-Face: Combining Collective and One-Sided Communication for Efficient Distributed SpMM;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2;2024-04-27

3. Distributed Graph Neural Network Training: A Survey;ACM Computing Surveys;2024-04-10

4. JITSPMM: Just-in-Time Instruction Generation for Accelerated Sparse Matrix-Matrix Multiplication;2024 IEEE/ACM International Symposium on Code Generation and Optimization (CGO);2024-03-02

5. Arrow Matrix Decomposition: A Novel Approach for Communication-Efficient Sparse Matrix Multiplication;Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming;2024-02-20

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