DONGARRA, Jack und LUSZCZEK, Piotr, 2026. HPL-Mx P benchmark: Mixed-precision algorithms, iterative refinement, and scalable data generation. International Journal of High Performance Computing Applications. 1 Januar 2026. Vol. 40, no. 1, p. 52-62. DOI 10.1177/10943420251382476.
Elsevier - Harvard (with titles)Dongarra, J., Luszczek, P., 2026. HPL-Mx P benchmark: Mixed-precision algorithms, iterative refinement, and scalable data generation. International Journal of High Performance Computing Applications 40, 52-62. https://doi.org/10.1177/10943420251382476
American Psychological Association 7th editionDongarra, J., & Luszczek, P. (2026). HPL-Mx P benchmark: Mixed-precision algorithms, iterative refinement, and scalable data generation. International Journal of High Performance Computing Applications, 40(1), 52-62. https://doi.org/10.1177/10943420251382476
Springer - Basic (author-date)Dongarra J, Luszczek P (2026) HPL-Mx P benchmark: Mixed-precision algorithms, iterative refinement, and scalable data generation.. International Journal of High Performance Computing Applications 40:52-62. https://doi.org/10.1177/10943420251382476
Juristische Zitierweise (Stüber) (Deutsch)Dongarra, Jack/ Luszczek, Piotr, HPL-Mx P benchmark: Mixed-precision algorithms, iterative refinement, and scalable data generation., International Journal of High Performance Computing Applications 2026, 52-62.