Publications

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Anzt, H., E. Chow, and J. Dongarra, “Iterative Sparse Triangular Solves for Preconditioning,” EuroPar 2015, Vienna, Austria, Springer Berlin, August 2015.  (322.36 KB)
Anzt, H., S. Tomov, M. Gates, J. Dongarra, and V. Heuveline, Block-asynchronous Multigrid Smoothers for GPU-accelerated Systems , no. UT-CS-11-689, December 2011.  (608.95 KB)
Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Orti, “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, August 2017.
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.  (1.08 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, October 2016.  (1.19 MB)
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.  (622.32 KB)
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., 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, February 2015.  (2.29 MB)
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, February 2016.  (565.34 KB)
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, April 2015.  (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., 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, October 2014.  (1.83 MB)
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, September 2017.  (1.28 MB)
Anzt, H., T. Cojean, C. Yen-Chen, J. Dongarra, G. Flegar, P. Nayak, S. Tomov, Y. M. Tsai, and W. Wang, “Load-Balancing Sparse Matrix Vector Product Kernels on GPUs,” ACM Transactions on Parallel Computing, vol. 7, issue 1, March 2020.  (5.67 MB)
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.  (4.2 MB)
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.  (1.24 MB)
Anzt, H., J. Dongarra, and E. S. Quintana-Orti, “Fine-grained Bit-Flip Protection for Relaxation Methods,” Journal of Computational Science, November 2016.  (1.47 MB)
Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Orti, “Variable-Size Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioning on Graphics Processors,” Parallel Computing, vol. 81, pp. 131-146, January 2019.  (1.9 MB)
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)
Anzt, H., S. Tomov, J. Dongarra, and V. Heuveline, “Weighted Block-Asynchronous Iteration on GPU-Accelerated Systems,” Tenth International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (Best Paper), Rhodes Island, Greece, August 2012.  (764.02 KB)
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, Oct 12, 2015.  (1.99 MB)
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, May 2016.  (285.28 KB)
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)
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. 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, November 2015.  (1.46 MB)
Anzt, H., T. Ribizel, G. Flegar, E. Chow, and J. Dongarra, “ParILUT – A Parallel Threshold ILU for GPUs,” IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, IEEE, May 2019.  (505.95 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, June 2015.  (2.03 MB)
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.  (721.84 KB)
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., E. Chow, and J. Dongarra, “On block-asynchronous execution on GPUs,” LAPACK Working Note, no. 291, November 2016.  (1.05 MB)
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)
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)
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., J. Dongarra, G. Flegar, N. J. Higham, and E. S. Quintana-Orti, “Adaptive Precision in Block-Jacobi Preconditioning for Iterative Sparse Linear System Solvers,” Concurrency and Computation: Practice and Experience, vol. 31, no. 6, pp. e4460, March 2019.  (341.54 KB)
Anzt, H., and J. Dongarra, “A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs,” SBAC-PAD, Lyon, France, IEEE, 2018.  (237.68 KB)
Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Orti, “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.  (552.62 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, 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, May 2016.
Antoniu, G., A. Costan, O. Marcu, M. S. Pérez, N. Stojanovic, R. M. Badia, M. Vázquez, S. Girona, M. Beck, T. Moore, et al., “A Collection of White Papers from the BDEC2 Workshop in Poznan, Poland,” Innovative Computing Laboratory Technical Report, no. ICL-UT-19-10: University of Tennessee, Knoxville, May 2019.  (5.82 MB)
Angskun, T., G. Fagg, G. Bosilca, J. Pjesivac–Grbovic, and J. Dongarra, “Self-Healing Network for Scalable Fault-Tolerant Runtime Environments,” Future Generation Computer Systems, vol. 26, no. 3, pp. 479-485, March 2010.  (1.54 MB)
Angskun, T., G. Bosilca, and J. Dongarra, “Binomial Graph: A Scalable and Fault- Tolerant Logical Network Topology,” Proceedings of The Fifth International Symposium on Parallel and Distributed Processing and Applications (ISPA07), Niagara Falls, Canada, Springer, August 2007.  (480.47 KB)
Angskun, T., G. Fagg, G. Bosilca, J. Pjesivac–Grbovic, and J. Dongarra, “Scalable Fault Tolerant Protocol for Parallel Runtime Environments,” 2006 Euro PVM/MPI, no. ICL-UT-06-12, Bonn, Germany, 00 2006.  (149.07 KB)
Angskun, T., G. Bosilca, G. Fagg, J. Pjesivac–Grbovic, and J. Dongarra, “Reliability Analysis of Self-Healing Network using Discrete-Event Simulation,” Proceedings of Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07): IEEE Computer Society, pp. 437-444, May 2007.
Angskun, T., G. Bosilca, B. Vander Zanden, and J. Dongarra, “Optimal Routing in Binomial Graph Networks,” The International Conference on Parallel and Distributed Computing, applications and Technologies (PDCAT), Adelaide, Australia, IEEE Computer Society, December 2007.
Angskun, T., G. Fagg, G. Bosilca, J. Pjesivac–Grbovic, and J. Dongarra, “Self-Healing Network for Scalable Fault Tolerant Runtime Environments,” DAPSYS 2006, 6th Austrian-Hungarian Workshop on Distributed and Parallel Systems, Innsbruck, Austria, January 2006.  (162.83 KB)
Angskun, T., G. Bosilca, and J. Dongarra, “Self-Healing in Binomial Graph Networks,” 2nd International Workshop On Reliability in Decentralized Distributed Systems (RDDS 2007), Vilamoura, Algarve, Portugal, November 2007.  (322.39 KB)
Andersson, U., and P. Mucci, “Analysis and Optimization of Yee_Bench using Hardware Performance Counters,” Proceedings of Parallel Computing 2005 (ParCo), Malaga, Spain, January 2005.  (72.27 KB)
Anderson, E., Z. Bai, C. Bischof, S. Blackford, J. Demmel, J. Dongarra, J. Du Croz, A. Greenbaum, S. Hammarling, A. McKenney, et al., “LAPACK Users' Guide, 3rd ed.,” Philadelphia: Society for Industrial and Applied Mathematics, January 1999.
Alvaro, W., J. Kurzak, and J. Dongarra, “Optimizing Matrix Multiplication for a Short-Vector SIMD Architecture - CELL Processor,” Parallel Computing, vol. 35, pp. 138-150, 00 2009.  (591.16 KB)
Alvaro, W., J. Kurzak, and J. Dongarra, “Fast and Small Short Vector SIMD Matrix Multiplication Kernels for the CELL Processor,” University of Tennessee Computer Science Technical Report, no. UT-CS-08-609, (also LAPACK Working Note 189), January 2008.  (500.99 KB)

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