Editorial for the special issue on architecture, algorithms and applications of high performance sparse matrix computations
Author:
Publisher
Springer Science and Business Media LLC
Subject
Information Systems,Hardware and Architecture,Computer Science Applications,Computer Science (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s42514-023-00157-9.pdf
Reference9 articles.
1. Asanovic, K., Bodik, R., Demmel, J., Keaveny, T., Keutzer, K., Kubiatowicz, J., Morgan, N., Patterson, D., Sen, K., Wawrzynek, J., Wessel, D., Yelick, K.: A view of the parallel computing landscape. Commun. ACM 52(10), 56–67 (2009). https://doi.org/10.1145/1562764.1562783
2. Bessant, Y.R.A., Jency, J.G., Sagayam, K.M., Jone, A.A.A., Pandey, D., Pandey, B.K.: Improved parallel matrix multiplication using Strassen and Urdhvatiryagbhyam method. CCF Trans. High Perform. Comput. (2023). https://doi.org/10.1007/s42514-023-00149-9
3. Gao, J., Chu, X., Wang, Y.: HeuriSPAI: a heuristic sparse approximate inverse preconditioning algorithm on GPU. CCF Trans. High Perform. Comput. (2023). https://doi.org/10.1007/s42514-023-00142-2
4. Li, S., Liao, X., Lu, Y., Roman, J.E., Yue, X.: A parallel structured banded DC algorithm for symmetric eigenvalue problems. CCF Trans. High Perform. Comput. (2022). https://doi.org/10.1007/s42514-022-00117-9
5. Li, Y., Wang, Z., Xie, H.: GCGE: a package for solving large scale eigenvalue problems by parallel block damping inverse power method. CCF Trans. High Perform. Comput. (2023). https://doi.org/10.1007/s42514-023-00135-1
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