ESSEX: Equipping Sparse Solvers For Exascale

Author:

Alappat Christie L.,Alvermann Andreas,Basermann Achim,Fehske Holger,Futamura Yasunori,Galgon Martin,Hager Georg,Huber Sarah,Imakura Akira,Kawai Masatoshi,Kreutzer Moritz,Lang Bruno,Nakajima Kengo,Röhrig-Zöllner Melven,Sakurai Tetsuya,Shahzad Faisal,Thies Jonas,Wellein Gerhard

Publisher

Springer International Publishing

Reference84 articles.

1. Alappat, C.L., Hager, G., Schenk, O., Thies, J., Basermann, A., Bishop, A.R., Fehske, H., Wellein, G.: A recursive algebraic coloring technique for hardware-efficient symmetric sparse matrix-vector multiplication. Accepted for publication in ACM Transactions on Parallel Computing. Preprint: http://arxiv.org/abs/1907.06487

2. Alvermann, A., Fehske, H.: Exciton mass and exciton spectrum in the cuprous oxide. J. Phys. B 51(4), 044001 (2018). https://doi.org/10.1088/1361-6455/aaa060 . http://stacks.iop.org/0953-4075/51/i=4/a=044001

3. Alvermann, A., Basermann, A., Fehske, H., Galgon, M., Hager, G., Kreutzer, M., Krämer, L., Lang, B., Pieper, A., Röhrig-Zöllner, M., Shahzad, F., Thies, J., Wellein, G.: ESSEX: equipping sparse solvers for exascale. In: Lopes, L. et al. (eds.) Euro-Par 2014: Parallel Processing Workshops. Lecture Notes in Computer Science, vol. 8806, pp. 577–588. Springer, Berlin (2014). http://doi.org/10.1007/978-3-319-14313-2_49

4. Alvermann, A., Basermann, A., Bungartz, H.J., Carbogno, C., Ernst, D., Fehske, H., Futamura, Y., Galgon, M., Hager, G., Huber, S., Huckle, T., Ida, A., Imakura, A., Kawai, M., Köcher, S., Kreutzer, M., Kus, P., Lang, B., Lederer, H., Manin, V., Marek, A., Nakajima, K., Nemec, L., Reuter, K., Rippl, M., Röhrig-Zöllner, M., Sakurai, T., Scheffler, M., Scheurer, C., Shahzad, F., Simoes Brambila, D., Thies, J., Wellein, G.: Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects. Jpn. J. Ind. Appl. Math. 36, 699–717 (2019). https://doi.org/10.1007/s13160-019-00360-8

5. Anzt, H., Tomov, S., Dongarra, J.: Accelerating the LOBPCG method on GPUs using a blocked sparse matrix vector product. University of Tennessee Innovative Computing Laboratory Technical Report UT-EECS-14-731 (2014). http://www.eecs.utk.edu/resources/library/589

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