Tuning Block Size for QR Factorization on CPU-GPU Hybrid Systems. - Yaohung M. Tsai; Weichung Wang; Ray-Bing Chen (MCSoC, 2012)

Adaptive block size for dense QR factorization in hybrid CPU-GPU systems via statistical modeling. - Ray-Bing Chen; Yaohung M. Tsai; Weichung Wang (Parallel Comput., 2014)

Performance-Portable Autotuning of OpenCL Kernels for Convolutional Layers of Deep Neural Networks. - Yaohung M. Tsai; Piotr Luszczek; Jakub Kurzak; Jack J. Dongarra (MLHPC@SC, 2016)

Autotuning Numerical Dense Linear Algebra for Batched Computation With GPU Hardware Accelerators. - Jack J. Dongarra; Mark Gates; Jakub Kurzak; Piotr Luszczek; Yaohung M. Tsai (Proc. IEEE, 2018)

Massively Parallel Automated Software Tuning. - Jakub Kurzak; Yaohung M. Tsai; Mark Gates; Ahmad Abdelfattah; Jack J. Dongarra (ICPP, 2019)

Scalable Data Generation for Evaluating Mixed-Precision Solvers. - Piotr Luszczek; Yaohung M. Tsai; Neil Lindquist; Hartwig Anzt; Jack J. Dongarra (HPEC, 2020)

A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic. - Ahmad Abdelfattah; Hartwig Anzt; Erik G. Boman; Erin C. Carson; Terry Cojean; Jack J. Dongarra; Mark Gates; Thomas Grützmacher; Nicholas J. Higham; Xiaoye Sherry Li; Neil Lindquist; Yang Liu 179; et al. (CoRR, 2020)

A survey of numerical linear algebra methods utilizing mixed-precision arithmetic. - Ahmad Abdelfattah; Hartwig Anzt; Erik G. Boman; Erin C. Carson; Terry Cojean; Jack J. Dongarra; Alyson Fox; Mark Gates; Nicholas J. Higham; Xiaoye S. Li; Jennifer A. Loe; Piotr Luszczek; et al. (Int. J. High Perform. Comput. Appl., 2021)

Mixed-Precision Algorithm for Finding Selected Eigenvalues and Eigenvectors of Symmetric and Hermitian Matrices1. - Yaohung M. Tsai; Piotr Luszczek; Jack J. Dongarra (ScalAH@SC, 2022)

Numerical eigen-spectrum slicing, accurate orthogonal eigen-basis, and mixed-precision eigenvalue refinement using OpenMP data-dependent tasks and accelerator offload. - Piotr Luszczek; Anthony Castaldo; Yaohung M. Tsai; Daniel Mishler; Jack J. Dongarra (Int. J. High Perform. Comput. Appl., 2024)