Efficient Execution of SpGEMM on Long Vector Architectures-Reference-Cited by-同舟云学术

Efficient Execution of SpGEMM on Long Vector Architectures

Published:2023-08-07 Issue: Volume: Page:
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Container-title:Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing
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Author:

Le Fèvre Valentin¹^ORCID,Casas Marc²^ORCID

Affiliation:

1. Barcelona Supercomputing Center, Barcelona, Spain

2. Barcelona Supercomputing Center, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3588195.3593000

Reference52 articles.

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2. Ilya Afanasyev and Vladimir V . Voevodin . 2020 . Developing Efficient Implementations of Connected Component Algorithms for NEC SX-Aurora TSUB-ASA. Lobachevskii Journal of Mathematics 41 (08 2020), 1417--1426. https://doi.org/10.1134/S1995080220080028 10.1134/S1995080220080028 Ilya Afanasyev and Vladimir V. Voevodin. 2020. Developing Efficient Implementations of Connected Component Algorithms for NEC SX-Aurora TSUB-ASA. Lobachevskii Journal of Mathematics 41 (08 2020), 1417--1426. https://doi.org/10.1134/S1995080220080028

3. Ilya V. Afanasyev , Vladimir V. Voevodin , Kazuhiko Komatsu , and Hiroaki Kobayashi . 2020. Developing an Efficient Vector-Friendly Implementation of the Breadth-First Search Algorithm for NEC SX-Aurora TSUBASA . In Parallel Computational Technologies, Leonid Sokolinsky and Mikhail Zymbler (Eds.). Springer International Publishing , Cham , 131--145. Ilya V. Afanasyev, Vladimir V. Voevodin, Kazuhiko Komatsu, and Hiroaki Kobayashi. 2020. Developing an Efficient Vector-Friendly Implementation of the Breadth-First Search Algorithm for NEC SX-Aurora TSUBASA. In Parallel Computational Technologies, Leonid Sokolinsky and Mikhail Zymbler (Eds.). Springer International Publishing, Cham, 131--145.

4. Exploiting Locality in Sparse Matrix-Matrix Multiplication on Many-Core Architectures

5. Partitioning Models for Scaling Parallel Sparse Matrix-Matrix Multiplication;Akbudak Kadir;ACM Trans. Parallel Comput.,2018

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