Publications

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Filters: Author is Thomas Gruetzmacher  [Clear All Filters]
2020
Anzt, H., T. Cojean, Y-C. Chen, F. Goebel, T. Gruetzmacher, P. Nayak, T. Ribizel, and Y-H. Tsai, “Ginkgo: A High Performance Numerical Linear Algebra Library,” Journal of Open Source Software, vol. 5, issue 52, August 2020. DOI: 10.21105/joss.02260  (721.84 KB)
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)
Abdelfattah, A., H. Anzt, E. Boman, E. Carson, T. Cojean, J. Dongarra, M. Gates, T. Gruetzmacher, N. J. Higham, S. Li, et al., “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)
2019
Gruetzmacher, T., T. Cojean, G. Flegar, F. Göbel, and H. Anzt, “A Customized Precision Format Based on Mantissa Segmentation for Accelerating Sparse Linear Algebra,” Concurrency and Computation: Practice and Experience, vol. 40319, issue 262, January 2019. DOI: 10.1002/cpe.5418
Anzt, H., G. Flegar, T. Gruetzmacher, and E. S. Quintana-Orti, “Toward a Modular Precision Ecosystem for High-Performance Computing,” The International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1069-1078, November 2019. DOI: 10.1177/1094342019846547  (1.93 MB)
2018
Anzt, H., T. Gruetzmacher, E. S. Quintana-Orti, and F. Scheidegger, “High-Performance GPU Implementation of PageRank with Reduced Precision based on Mantissa Segmentation,” 8th Workshop on Irregular Applications: Architectures and Algorithms, 2018.
Anzt, H., J. Dongarra, G. Flegar, and T. Gruetzmacher, “Variable-Size Batched Condition Number Calculation on GPUs,” SBAC-PAD, Lyon, France, September 2018.  (509.3 KB)