Publications

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Anzt, H., T. Cojean, Y-C. Chen, F. Goebel, T. Gruetzmacher, P. Nayak, T. Ribizel, Y-H. Tsai, and J. Dongarra, Ginkgo: A Node-Level Sparse Linear Algebra Library for HPC (Poster) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (699 KB)
Anzt, H., M. Gates, J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, “Preconditioned Krylov Solvers on GPUs,” Parallel Computing, June 2017.  (1.19 MB)
Anzt, H., S. Tomov, J. Dongarra, and V. Heuveline, “A Block-Asynchronous Relaxation Method for Graphics Processing Units,” University of Tennessee Computer Science Technical Report, no. UT-CS-11-687 / LAWN 258, November 2011.  (1.08 MB)
Anzt, H., M. Kreutzer, E. Ponce, G. D. Peterson, G. Wellein, and J. Dongarra, “Optimization and Performance Evaluation of the IDR Iterative Krylov Solver on GPUs,” The International Journal of High Performance Computing Applications, vol. 32, no. 2, pp. 220–230, March 2018.  (2.08 MB)
Anzt, H., and E. S. Quintana-Orti, “Improving the Energy Efficiency of Sparse Linear System Solvers on Multicore and Manycore Systems,” Philosophical Transactions of the Royal Society A -- Mathematical, Physical and Engineering Sciences, vol. 372, issue 2018, July 2014.  (779.57 KB)
Anzt, H., J. Dongarra, and E. S. Quintana-Orti, “Adaptive Precision Solvers for Sparse Linear Systems,” 3rd International Workshop on Energy Efficient Supercomputing (E2SC '15), Austin, TX, ACM, November 2015.
Anzt, H., T. Cojean, and E. Kuhn, “Towards a New Peer Review Concept for Scientific Computing ensuring Technical Quality, Software Sustainability, and Result Reproducibility,” Proceedings in Applied Mathematics and Mechanics, vol. 19, issue 1, November 2019.

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