Publications
A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic,”
SLATE Working Notes, no. 15, ICL-UT-20-08: University of Tennessee, July 2020.
(3.98 MB)
“Mixed-Precision Solution of Linear Systems Using Accelerator-Based Computing,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-20-05: University of Tennessee, May 2020.
(1.03 MB)
“Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification
, July 2018.
(483.05 KB)
A Set of Batched Basic Linear Algebra Subprograms,”
ACM Transactions on Mathematical Software, October 2020.
“Numerical Algorithms for High-Performance Computational Science,”
Philosophical Transactions of the Royal Society A, vol. 378, issue 2166, 2020.
DOI: 10.1098/rsta.2019.0066 (724.37 KB)
“Mixed-Precision Iterative Refinement using Tensor Cores on GPUs to Accelerate Solution of Linear Systems,”
Proceedings of the Royal Society A, vol. 476, issue 2243, November 2020.
DOI: 10.1098/rspa.2020.0110 (2.24 MB)
“Adaptive Precision in Block-Jacobi Preconditioning for Iterative Sparse Linear System Solvers,”
Concurrency and Computation: Practice and Experience, vol. 31, no. 6, pp. e4460, March 2019.
DOI: 10.1002/cpe.4460 (341.54 KB)
“Optimized Batched Linear Algebra for Modern Architectures,”
Euro-Par 2017, Santiago de Compostela, Spain, Springer, August 2017.
DOI: 10.1007/978-3-319-64203-1_37 (618.33 KB)
“Harnessing GPU Tensor Cores for Fast FP16 Arithmetic to Speed up Mixed-Precision Iterative Refinement Solvers,”
The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Dallas, TX, IEEE, November 2018.
DOI: 10.1109/SC.2018.00050 (642.51 KB)
“The Design and Performance of Batched BLAS on Modern High-Performance Computing Systems,”
International Conference on Computational Science (ICCS 2017), Zürich, Switzerland, Elsevier, June 2017.
DOI: DOI:10.1016/j.procs.2017.05.138 (446.14 KB)
“High-Performance Computing,”
The Princeton Companion to Applied Mathematics, Princeton, New Jersey, Princeton University Press, pp. 839-842, 2015.
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