Effect of Mixed Precision Computing on H-Matrix Vector Multiplication in BEM Analysis

Author:

Ooi Rise1,Iwashita Takeshi1,Fukaya Takeshi1,Ida Akihiro2,Yokota Rio3

Affiliation:

1. Hokkaido University

2. The University of Tokyo

3. Tokyo Institute of Technology

Funder

Japan Society for the Promotion of Science

High Performance Computing Infrastructure

JSPS KAKENHI

Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures

Publisher

ACM

Reference28 articles.

1. 2019. IEEE Standard for Floating-Point Arithmetic. IEEE Std 754-2019 (Revision of IEEE 754-2008) (July 2019) 1--84. https://doi.org/10.1109/IEEESTD.2019.8766229 2019. IEEE Standard for Floating-Point Arithmetic. IEEE Std 754-2019 (Revision of IEEE 754-2008) (July 2019) 1--84. https://doi.org/10.1109/IEEESTD.2019.8766229

2. Fast Batched Matrix Multiplication for Small Sizes Using Half-Precision Arithmetic on GPUs

3. C.A. Brebbia J.C.F. Telles and L.C. Wrobel. 1984. Boundary element techniques: theory and applications in engineering. Springer-Verlag. https://books.google.co.jp/books?id=HpwQAQAAMAAJ C.A. Brebbia J.C.F. Telles and L.C. Wrobel. 1984. Boundary element techniques: theory and applications in engineering. Springer-Verlag. https://books.google.co.jp/books?id=HpwQAQAAMAAJ

4. Mixed Precision Iterative Refinement Techniques for the Solution of Dense Linear Systems

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2. Mixed precision low-rank approximations and their application to block low-rank LU factorization;IMA Journal of Numerical Analysis;2022-08-23

3. Low/Adaptive Precision Computation in Preconditioned Iterative Solvers for Ill-Conditioned Problems;International Conference on High Performance Computing in Asia-Pacific Region;2022-01-07

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