SAGE: A Storage-Based Approach for Scalable and Efficient Sparse Generalized Matrix-Matrix Multiplication
Author:
Affiliation:
1. Hanyang University, Seoul, Republic of Korea
2. Yonsei University, Seoul, Republic of Korea
Funder
The Korea government (Ministry of Science and ICT)
Samsung Electronics Co., Ltd
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3583780.3615044
Reference49 articles.
1. Exploiting Locality in Sparse Matrix-Matrix Multiplication on Many-Core Architectures
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3. Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication
4. Daehyeon Baek Soojin Hwang Taekyung Heo Daehoon Kim and Jaehyuk Huh. 2021. InnerSP: A Memory Efficient Sparse Matrix Multiplication Accelerator with Locality-Aware Inner Product Processing. In 2021 30th International Conference on Parallel Architectures and Compilation Techniques (PACT). IEEE 116--128. Daehyeon Baek Soojin Hwang Taekyung Heo Daehoon Kim and Jaehyuk Huh. 2021. InnerSP: A Memory Efficient Sparse Matrix Multiplication Accelerator with Locality-Aware Inner Product Processing. In 2021 30th International Conference on Parallel Architectures and Compilation Techniques (PACT). IEEE 116--128.
5. Efficient semi-streaming algorithms for local triangle counting in massive graphs
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