Publications
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Filters: Author is Hartwig Anzt [Clear All Filters]
Acceleration of GPU-based Krylov solvers via Data Transfer Reduction,”
International Journal of High Performance Computing Applications, 2015.
“Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse and Batched Computations,”
2020 IEEE/ACM Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS): IEEE, November 2020.
(1.9 MB)
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Experiences in Autotuning Matrix Multiplication for Energy Minimization on GPUs,”
Concurrency and Computation: Practice and Experience, vol. 27, issue 17, pp. 5096 - 5113, Oct 12, 2015.
DOI: 10.1002/cpe.3516
(1.99 MB)
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Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioner Generation on GPUs,”
Proceedings of the 8th International Workshop on Programming Models and Applications for Multicores and Manycores, New York, NY, USA, ACM, pp. 1–10, February 2017.
DOI: 10.1145/3026937.3026940
(552.62 KB)
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Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures,”
VECPAR 2014, Eugene, OR, June 2014.
(430.56 KB)
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Solver Interface & Performance on Cori,”
Innovative Computing Laboratory Technical Report, no. ICL-UT-18-05: University of Tennessee, June 2018.
(188.05 KB)
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