Publications

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Anzt, H., and J. Dongarra, “A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs,” SBAC-PAD, Lyon, France, IEEE, 2018.  (237.68 KB)
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Anzt, H., T. Huckle, J. Bräckle, and J. Dongarra, “Incomplete Sparse Approximate Inverses for Parallel Preconditioning,” Parallel Computing, vol. 71, pp. 1–22, January 2018. DOI: 10.1016/j.parco.2017.10.003  (1.24 MB)
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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.
Newburn, C. J., G. Bansal, M. Wood, L. Crivelli, J. Planas, A. Duran, P. Souza, L. Borges, P. Luszczek, S. Tomov, et al., “Heterogeneous Streaming,” The Sixth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2016, Chicago, IL, IEEE, May 2016.  (2.73 MB)
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Abdelfattah, A., S. Tomov, P. Luszczek, H. Anzt, and J. Dongarra, “GPU-based LU Factorization and Solve on Batches of Matrices with Band Structure,” SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, CO, ACM, November 2023. DOI: 10.1145/3624062.3624247
Anzt, H., P. Luszczek, J. Dongarra, and V. Heuveline, “GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement,” EuroPar 2012 (also LAWN 260), Rhodes Island, Greece, August 2012.  (662.98 KB)
Cojean, T., Y-H. Mike Tsai, and H. Anzt, “Ginkgo—A math library designed for platform portability,” Parallel Computing, vol. 111, pp. 102902, February 2022. DOI: 10.1016/j.parco.2022.102902
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., T. Cojean, G. Flegar, F. Göbel, T. Grützmacher, P. Nayak, T. Ribizel, Y. Mike Tsai, and E. S. Quintana-Ortí, “Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing,” ACM Transactions on Mathematical Software, vol. 48, issue 12, pp. 1 - 33, March 2022. DOI: 10.1145/3480935  (4.2 MB)
Cojean, T., P. Nayak, T. Ribizel, N. Beams, Y-H. Mike Tsai, M. Koch, F. Göbel, T. Grützmacher, and H. Anzt, “Ginkgo - A math library designed to accelerate Exascale Computing Project science applications,” The International Journal of High Performance Computing Applications, August 2024. DOI: 10.1177/10943420241268323
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., N. Beams, T. Cojean, F. Göbel, T. Grützmacher, A. Kashi, P. Nayak, T. Ribizel, and Y. M. Tsai, Gingko: A Sparse Linear Algebrea Library for HPC : 2021 ECP Annual Meeting, April 2021.  (893.04 KB)
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Anzt, H., G. Collins, J. Dongarra, G. Flegar, and E. S. Quintana-Orti, “Flexible Batched Sparse Matrix-Vector Product on GPUs,” 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA '17), Denver, CO, ACM Press, November 2017. DOI: http://dx.doi.org/10.1145/3148226.3148230  (583.4 KB)
Anzt, H., G. Collins, J. Dongarra, G. Flegar, and E. S. Quintana-Orti, Flexible Batched Sparse Matrix Vector Product on GPUs , Denver, Colorado, ScalA'17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, November 2017.  (16.8 MB)
Anzt, H., J. Dongarra, and E. S. Quintana-Orti, “Fine-grained Bit-Flip Protection for Relaxation Methods,” Journal of Computational Science, November 2016. DOI: 10.1016/j.jocs.2016.11.013  (1.47 MB)
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Anzt, H., Y. M. Tsai, A. Abdelfattah, T. Cojean, and J. Dongarra, “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)
Nayak, P., T. Cojean, and H. Anzt, “Evaluating Asynchronous Schwarz Solvers on GPUs,” International Journal of High Performance Computing Applications, August 2020. DOI: 10.1177/1094342020946814
Hoefler, T., B. Stevens, A. F. Prein, J. Baehr, T. Schulthess, T. F. Stocker, J. Taylor, D. Klocke, P. Manninen, P. M. Forster, et al., Earth Virtualization Engines - A Technical Perspective , September 2023.
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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
Aliaga, J. I., H. Anzt, T. Grützmacher, E. S. Quintana-Orti, and A. E. Thomas, “Compression and load balancing for efficient sparse matrix‐vector product on multicore processors and graphics processing units,” Concurrency and Computation: Practice and Experience, vol. 34, issue 14, June 2022. DOI: 10.1002/cpe.6515  (749.82 KB)
Aliaga, J. I., H. Anzt, T. Grützmacher, E. S. Quintana-Ortí, and A. E. Thomas, “Compressed basis GMRES on high-performance graphics processing units,” The International Journal of High Performance Computing Applications, May 2022. DOI: 10.1177/10943420221115140  (13.52 MB)
Gates, M., S. Tomov, H. Anzt, P. Luszczek, and J. Dongarra, Clover: Computational Libraries Optimized via Exascale Research , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (872 KB)
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Anzt, H., J. Dongarra, M. Gates, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, “Bringing High Performance Computing to Big Data Algorithms,” Handbook of Big Data Technologies: Springer, 2017. DOI: 10.1007/978-3-319-49340-4  (1.22 MB)
Anzt, H., S. Tomov, J. Dongarra, and V. Heuveline, “A Block-Asynchronous Relaxation Method for Graphics Processing Units,” Journal of Parallel and Distributed Computing, vol. 73, issue 12, pp. 1613–1626, December 2013. DOI: http://dx.doi.org/10.1016/j.jpdc.2013.05.008  (1.08 MB)
Anzt, H., S. Tomov, M. Gates, J. Dongarra, and V. Heuveline, “Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems,” ICCS 2012, Omaha, NE, June 2012.  (608.95 KB)
Kashi, A., P. Nayak, D. Kulkarni, A. Scheinberg, P. Lin, and H. Anzt, “Batched sparse iterative solvers on GPU for the collision operator for fusion plasma simulations,” 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), Lyon, France, IEEE, July 2022. DOI: 10.1109/IPDPS53621.2022.00024  (1.26 MB)
Luszczek, P., A. Abdelfattah, H. Anzt, A. Suzuki, and S. Tomov, “Batched sparse and mixed-precision linear algebra interface for efficient use of GPU hardware accelerators in scientific applications,” Future Generation Computer Systems, vol. 160, pp. 359 - 374, November 2024. DOI: 10.1016/j.future.2024.06.004
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Anzt, H., and G. Flegar, “Are we Doing the Right Thing? – A Critical Analysis of the Academic HPC Community,” 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Rio de Janeiro, Brazil, IEEE, May 2019. DOI: 10.1109/IPDPSW.2019.00122  (622.32 KB)
Anzt, H., M. Casas, C. I. Malossi, E. S. Quintana-Ortí, F. Scheidegger, and S. Zhuang, “Approximate Computing for Scientific Applications,” Approximate Computing Techniques, 322: Springer International Publishing, pp. 415 - 465, January 2022. DOI: 10.1007/978-3-030-94705-7_14
Ribizel, T., and H. Anzt, “Approximate and Exact Selection on GPUs,” 2019 IEEE International Parallel and Distributed Processing Symposium Workshops, Rio de Janeiro, Brazil, IEEE, May 2019. DOI: 10.1109/IPDPSW.2019.00088  (440.71 KB)

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