Infinite-Precision Inner Product and Sparse Matrix-Vector Multiplication Using Ozaki Scheme with Dot2 on Manycore Processors-Reference-Cited by-同舟云学术

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Infinite-Precision Inner Product and Sparse Matrix-Vector Multiplication Using Ozaki Scheme with Dot2 on Manycore Processors

Published:2023 Issue: Volume: Page:40-54
ISSN:0302-9743
Container-title:Parallel Processing and Applied Mathematics
language:
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Author:

Mukunoki Daichi^ORCID,Ozaki Katsuhisa^ORCID,Ogita Takeshi^ORCID,Imamura Toshiyuki^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-30442-2_4

Reference28 articles.

1. Arteaga, A., Fuhrer, O., Hoefler, T.: Designing bit-reproducible portable high-performance applications. In: Proceedings of IEEE 28th International Parallel and Distributed Processing Symposium (IPDPS 2014), pp. 1235–1244 (2014). https://doi.org/10.1109/IPDPS.2014.127

2. Bell, N., Garland, M.: Implementing sparse matrix-vector multiplication on throughput-oriented processors. In: Proceedings of International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2009), pp. 1–11. No. 18 (2009). https://doi.org/10.1145/1654059.1654078

3. Briggs, K.: Implementing exact real arithmetic in python, c++ and c. Theoret. Comput. Sci. 351(1), 74–81 (2006). https://doi.org/10.1016/j.tcs.2005.09.058

4. Chohra, C., Langlois, P., Parello, D.: Reproducible, accurately rounded and efficient BLAS. In: 22nd International European Conference on Parallel and Distributed Computing (Euro-Par 2016), pp. 609–620 (2016). https://doi.org/10.1007/978-3-319-58943-5_49

5. Collange, S., Defour, D., Graillat, S., Iakymchuk, R.: Numerical reproducibility for the parallel reduction on multi- and many-core architectures. Parallel Comput. 49, 83–97 (2015). https://doi.org/10.1016/j.parco.2015.09.001

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