Publications

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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, 2019-01. DOI: 10.1002/cpe.5418
Jagode, H., A. Danalis, H. Anzt, and J. Dongarra, PAPI Software-Defined Events for in-Depth Performance Analysis,” The International Journal of High Performance Computing Applications, 2019.  (442.39 KB)
Anzt, H., G. Flegar, T. Grützmacher, and E. S. Quintana-Ortí, Toward a Modular Precision Ecosystem for High-Performance Computing,” The International Journal of High Performance Computing Applications, 2019-09. DOI: 10.1177/1094342019846547  (1.93 MB)
2018
Anzt, H., J. Dongarra, G. Flegar, N. J. Higham, and E. S. Quintana-Ortí, Adaptive Precision in Block‐Jacobi Preconditioning for Iterative Sparse Linear System Solvers,” Concurrency Computation: Practice and Experience, 2018-03. DOI: 10.1002/cpe.4460
Anzt, H., T. Huckle, J. Bräckle, and J. Dongarra, Incomplete Sparse Approximate Inverses for Parallel Preconditioning,” Parallel Computing, vol. 71, pp. 1–22, 2018-01. DOI: 10.1016/j.parco.2017.10.003
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, 2018-03. DOI: 10.1177/1094342016646844  (2.08 MB)
Anzt, H., E. Chow, and J. Dongarra, ParILUT - A New Parallel Threshold ILU,” SIAM Journal on Scientific Computing, vol. 40, issue 4: SIAM, pp. C503–C519, 2018-07. DOI: 10.1137/16M1079506  (19.26 MB)
Jagode, H., A. Danalis, H. Anzt, I. Yamazaki, M. Hoemmen, E. Boman, S. Tomov, and J. Dongarra, Software-Defined Events (SDEs) in MAGMA-Sparse,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-12: University of Tennessee, 2018-12.  (481.69 KB)
Anzt, H., I. Yamazaki, M. Hoemmen, E. Boman, and J. Dongarra, Solver Interface & Performance on Cori,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-05: University of Tennessee, 2018-06.  (188.05 KB)
Chow, E., H. Anzt, J. Scott, and J. Dongarra, Using Jacobi Iterations and Blocking for Solving Sparse Triangular Systems in Incomplete Factorization Preconditioning,” Journal of Parallel and Distributed Computing, vol. 119, pp. 219–230, 2018-11. DOI: 10.1016/j.jpdc.2018.04.017  (273.53 KB)
Anzt, H., J. Dongarra, G. Flegar, and T. Gruetzmacher, Variable-Size Batched Condition Number Calculation on GPUs,” SBAC-PAD, Lyon, France, 2018-09.  (509.3 KB)
Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, Variable-Size Batched Gauss–Jordan Elimination for Block-Jacobi Preconditioning on Graphics Processors,” Parallel Computing, 2018-01. DOI: 10.1016/j.parco.2017.12.006  (1.9 MB)
2017
Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, 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, 2017-02. DOI: 10.1145/3026937.3026940  (552.62 KB)
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
Anzt, H., G. Collins, J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, Flexible Batched Sparse Matrix Vector Product on GPUs , Denver, Colorado, ScalA'17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, 2017-11.  (16.8 MB)
Anzt, H., G. Collins, J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, Flexible Batched Sparse Matrix-Vector Product on GPUs,” Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA '17), Denver, Colorado, ACM Press, 2017-11. DOI: 10.1145/3148226.3148230
Anzt, H., E. Boman, J. Dongarra, G. Flegar, M. Gates, M. Heroux, M. Hoemmen, J. Kurzak, P. Luszczek, S. Rajamanickam, et al., MAGMA-sparse Interface Design Whitepaper,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-05, 2017-09.  (1.28 MB)
Anzt, H., M. Gates, J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, Preconditioned Krylov Solvers on GPUs,” Parallel Computing, 2017-06. DOI: 10.1016/j.parco.2017.05.006
Abdelfattah, A., H. Anzt, A. Bouteiller, A. Danalis, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, et al., Roadmap for the Development of a Linear Algebra Library for Exascale Computing: SLATE: Software for Linear Algebra Targeting Exascale,” SLATE Working Notes, no. 1, ICL-UT-17-02: Innovative Computing Laboratory, University of Tennessee, 2017-06.  (2.8 MB)
Anzt, H., J. Dongarra, G. Flegar, E. S. Quintana-Ortí, and A. E. Thomas, Variable-Size Batched Gauss-Huard for Block-Jacobi Preconditioning,” International Conference on Computational Science (ICCS 2017), vol. 108, Zurich, Switzerland, Procedia Computer Science, pp. 1783-1792, 2017-06.
Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, Variable-Size Batched LU for Small Matrices and Its Integration into Block-Jacobi Preconditioning,” 46th International Conference on Parallel Processing (ICPP), Bristol, United Kingdom, IEEE, 2017-08. DOI: 10.1109/ICPP.2017.18
2016
Anzt, H., M. Baboulin, J. Dongarra, Y. Fournier, F. Hulsemann, A. Khabou, and Y. Wang, Accelerating the Conjugate Gradient Algorithm with GPU in CFD Simulations,” VECPAR, 2016.
Anzt, H., E. Chow, T. Huckle, and J. Dongarra, Batched Generation of Incomplete Sparse Approximate Inverses on GPUs,” Proceedings of the 7th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, pp. 49–56, 2016-11. DOI: 10.1109/ScalA.2016.11
Anzt, H., E. Chow, and J. Dongarra, On block-asynchronous execution on GPUs,” LAPACK Working Note, no. 291, 2016-11.  (1.05 MB)
Anzt, H., E. Chow, D. Szyld, and J. Dongarra, Domain Overlap for Iterative Sparse Triangular Solves on GPUs,” Software for Exascale Computing - SPPEXA, vol. 113: Springer International Publishing, pp. 527–545, 2016-09. DOI: 10.1007/978-3-319-40528-5_24
Anzt, H., J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, Efficiency of General Krylov Methods on GPUs – An Experimental Study,” The Sixth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), Chicago, IL, IEEE, 2016-05. DOI: 10.1109/IPDPSW.2016.45  (285.28 KB)
Anzt, H., J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, Efficiency of General Krylov Methods on GPUs – An Experimental Study,” 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 683-691, 2016-05. DOI: 10.1109/IPDPSW.2016.45
Anzt, H., , and E. S. Quintana-Ortí, Fine-grained Bit-Flip Protection for Relaxation Methods,” Journal of Computational Science, 2016-11. DOI: 10.1016/j.jocs.2016.11.013
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, 2016-05.  (2.73 MB)
Anzt, H., S. Tomov, and J. Dongarra, On the performance and energy efficiency of sparse linear algebra on GPUs,” International Journal of High Performance Computing Applications, 2016-10. DOI: 10.1177/1094342016672081
Anzt, H., E. Chow, J. Saak, and J. Dongarra, Updating Incomplete Factorization Preconditioners for Model Order Reduction,” Numerical Algorithms, vol. 73, issue 3, no. 3, pp. 611–630, 2016-02. DOI: 10.1007/s11075-016-0110-2  (565.34 KB)
2015
Gates, M., H. Anzt, J. Kurzak, and J. Dongarra, Accelerating Collaborative Filtering for Implicit Feedback Datasets using GPUs,” 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, IEEE, 2015-11.  (1.02 MB)
Anzt, H., S. Tomov, and J. Dongarra, Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product,” Spring Simulation Multi-Conference 2015 (SpringSim'15), Alexandria, VA, SCS, 2015-04.  (1.46 MB)
Anzt, H., W. Sawyer, S. Tomov, P. Luszczek, and J. Dongarra, Acceleration of GPU-based Krylov solvers via Data Transfer Reduction,” International Journal of High Performance Computing Applications, 2015.
Anzt, H., J. Dongarra, and E. S. Quintana-Ortí, Adaptive Precision Solvers for Sparse Linear Systems,” 3rd International Workshop on Energy Efficient Supercomputing (E2SC '15), Austin, TX, ACM, 2015-11.
Chow, E., H. Anzt, and J. Dongarra, Asynchronous Iterative Algorithm for Computing Incomplete Factorizations on GPUs,” International Supercomputing Conference (ISC 2015), Frankfurt, Germany, 2015-07.
Anzt, H., S. Tomov, and J. Dongarra, Energy Efficiency and Performance Frontiers for Sparse Computations on GPU Supercomputers,” Sixth International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM '15), San Francisco, CA, ACM, 2015-02. DOI: 10.1145/2712386.2712387  (2.29 MB)
Anzt, H., B. Haugen, J. Kurzak, P. Luszczek, and J. Dongarra, Experiences in autotuning matrix multiplication for energy minimization on GPUs,” Concurrency in Computation: Practice and Experience, vol. 27, issue 17, pp. 5096-5113, 2015-12. DOI: 10.1002/cpe.3516  (1.98 MB)
Anzt, H., B. Haugen, J. Kurzak, P. Luszczek, and J. Dongarra, Experiences in Autotuning Matrix Multiplication for Energy Minimization on GPUs,” Concurrency and Computation: Practice and Experience, vol. 27, issue 17, pp. 5096 - 5113, December Oct, 2015. DOI: 10.1002/cpe.3516  (1.99 MB)
Anzt, H., E. Ponce, G. D. Peterson, and J. Dongarra, GPU-accelerated Co-design of Induced Dimension Reduction: Algorithmic Fusion and Kernel Overlap,” 2nd International Workshop on Hardware-Software Co-Design for High Performance Computing, Austin, TX, ACM, 2015-11.  (1.46 MB)
Kurzak, J., H. Anzt, M. Gates, and J. Dongarra, Implementation and Tuning of Batched Cholesky Factorization and Solve for NVIDIA GPUs,” IEEE Transactions on Parallel and Distributed Systems, no. 1045-9219, 2015-11.
Anzt, H., E. Chow, and J. Dongarra, Iterative Sparse Triangular Solves for Preconditioning,” EuroPar 2015, Vienna, Austria, Springer Berlin, 2015-08. DOI: 10.1007/978-3-662-48096-0_50  (322.36 KB)
Anzt, H., J. Dongarra, M. Gates, A. Haidar, K. Kabir, P. Luszczek, S. Tomov, and I. Yamazaki, MAGMA MIC: Optimizing Linear Algebra for Intel Xeon Phi , Frankfurt, Germany, ISC High Performance (ISC15), Intel Booth Presentation, 2015-06.  (2.03 MB)
Anzt, H., E. Chow, D. Szyld, and J. Dongarra, Random-Order Alternating Schwarz for Sparse Triangular Solves,” 2015 SIAM Conference on Applied Linear Algebra (SIAM LA), Atlanta, GA, SIAM, 2015-10.  (1.53 MB)
Anzt, H., J. Dongarra, and E. S. Quintana-Ortí, Tuning Stationary Iterative Solvers for Fault Resilience,” 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA15), Austin, TX, ACM, 2015-11.  (1.28 MB)
2014
Anzt, H., S. Tomov, and J. Dongarra, Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product,” University of Tennessee Computer Science Technical Report, no. UT-EECS-14-731: University of Tennessee, 2014-10.  (1.83 MB)
Lukarski, D., H. Anzt, S. Tomov, and J. Dongarra, Hybrid Multi-Elimination ILU Preconditioners on GPUs,” International Heterogeneity in Computing Workshop (HCW), IPDPS 2014, Phoenix, AZ, IEEE, 2014-05.  (1.67 MB)
Anzt, H., S. Tomov, and J. Dongarra, Implementing a Sparse Matrix Vector Product for the SELL-C/SELL-C-σ formats on NVIDIA GPUs,” University of Tennessee Computer Science Technical Report, no. UT-EECS-14-727: University of Tennessee, 2014-04.  (578.11 KB)
Anzt, H., and E. S. Quintana-Ortí, 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, 2014-07. DOI: 10.1098/rsta.2013.0279  (779.57 KB)
Yamazaki, I., H. Anzt, S. Tomov, M. Hoemmen, and J. Dongarra, Improving the performance of CA-GMRES on multicores with multiple GPUs,” IPDPS 2014, Phoenix, AZ, IEEE, 2014-05.  (333.82 KB)

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