Publications

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A
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., 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, ParILUT - A New Parallel Threshold ILU,” SIAM Journal on Scientific Computing, vol. 40, issue 4: SIAM, pp. C503–C519, July 2018. DOI: 10.1137/16M1079506  (19.26 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., 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., 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, February 2017. DOI: 10.1145/3026937.3026940  (552.62 KB)
Anzt, H., Y. Chen Chen, T. Cojean, J. Dongarra, G. Flegar, P. Nayak, E. S. Quintana-Ortí, Y. M. Tsai, and W. Wang, Towards Continuous Benchmarking,” Platform for Advanced Scientific Computing Conference (PASC 2019), Zurich, Switzerland, ACM Press, June 2019. DOI: 10.1145/3324989.3325719  (1.51 MB)
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, June 2018.  (188.05 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, May 2016. DOI: 10.1109/IPDPSW.2016.45
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, November 2015.
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, December 2015. DOI: 10.1002/cpe.3516  (1.98 MB)
Anzt, H., M. Gates, J. Dongarra, M. Kreutzer, G. Wellein, and M. Kohler, Preconditioned Krylov Solvers on GPUs,” Parallel Computing, June 2017. DOI: 10.1016/j.parco.2017.05.006
Anzt, H., D. Lukarski, S. Tomov, and J. Dongarra, Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures,” VECPAR 2014, Eugene, OR, June 2014.  (430.56 KB)
Anzt, H., P. Luszczek, J. Dongarra, and V. Heuveline, GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement,” University of Tennessee Computer Science Technical Report UT-CS-11-690 (also Lawn 260), December 2011.  (662.98 KB)
Anzt, H., G. Flegar, T. Gruetzmacher, and E. S. Quintana-Ortí, 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)
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. DOI: 10.1002/pamm.201900490
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, August 2017. DOI: 10.1109/ICPP.2017.18
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, November 2016. DOI: 10.1109/ScalA.2016.11
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, November 2015.  (1.28 MB)
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, July 2014. DOI: 10.1098/rsta.2013.0279  (779.57 KB)
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)
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)
Arbenz, P., A. Cleary, J. Dongarra, and M. Hegland, A Comparison of Parallel Solvers for General Narrow Banded Linear Systems,” Parallel and Distributed Computing Practices, vol. 2, pp. 385-400, October 2002.  (304.96 KB)
Arbenz, P., A. Cleary, J. Dongarra, and M. Hegland, A Comparison of Parallel Solvers for General Narrow Banded Linear Systems (LAPACK Working Note 142),” University of Tennessee Computer Science Technical Report, no. UT-CS-99-414, January 1999.  (304.96 KB)
Arbenz, P., A. Cleary, J. Dongarra, and M. Hegland, A Comparison of Parallel Solvers for Diagonally Dominant and General Narrow Banded Linear Systems II (LAPACK Working Note 143),” University of Tennessee Computer Science Department Technical Report, no. UT-CS-99-415, January 1999.  (174.46 KB)
Arnold, D., S. Blackford, J. Dongarra, V. Eijkhout, and T. Xu, Seamless Access to Adaptive Solver Algorithms,” Proceedings of 16th IMACS World Congress 2000 on Scientific Computing, Applications Mathematics and Simulation, Lausanne, Switzerland, August 2000.  (151.42 KB)
Arnold, D., W. Lee, J. Dongarra, and M. Wheeler, Providing Infrastructure and Interface to High Performance Applications in a Distributed Setting,” ASTC-HPC 2000, Washington, DC, April 2000.  (96.04 KB)
Arnold, D., D. Bachmann, and J. Dongarra, Request Sequencing: Optimizing Communication for the Grid,” Lecture Notes in Computer Science: Proceedings of 6th International Euro-Par Conference 2000, Parallel Processing, (Germany: Springer Verlag 2000), pp. V1900,1213-1222, January 2000.  (165.92 KB)
Arnold, D., H. Casanova, and J. Dongarra, Innovations of the NetSolve Grid Computing System,” Concurrency: Practice and Experience, vol. 14, no. 13-15, pp. 1457-1479, January 2002.  (311.31 KB)
Arnold, D., and J. Dongarra, The NetSolve Environment: Progressing Towards the Seamless Grid,” 2000 International Conference on Parallel Processing (ICPP-2000), Toronto, Canada, August 2000.  (148.85 KB)
Arnold, D., S. Vadhiyar, and J. Dongarra, On the Convergence of Computational and Data Grids,” Parallel Processing Letters, vol. 11, no. 2-3, pp. 187-202, January 2001.  (213.35 KB)
Arnold, D., and J. Dongarra, Developing an Architecture to Support the Implementation and Development of Scientific Computing Applications,” to appear in Proceedings of Working Conference 8: Software Architecture for Scientific Computing Applications, Ottawa, Canada, October 2000.  (176.25 KB)
Arnold, D., S. Browne, J. Dongarra, G. Fagg, and K. Moore, Secure Remote Access to Numerical Software and Computational Hardware,” Proceedings of the DoD HPC Users Group Conference (HPCUG) 2000, Albuquerque, NM, June 2000.  (172.6 KB)
Arnold, D., S. Browne, J. Dongarra, G. Fagg, and K. Moore, Secure Remote Access to Numerical Software and Computation Hardware,” University of Tennessee Computer Science Technical Report, UT-CS-00-446, July 2000.  (402.31 KB)
Asch, M., T. Moore, R. M. Badia, M. Beck, P. Beckman, T. Bidot, F. Bodin, F. Cappello, A. Choudhary, B. R. de Supinski, et al., Big Data and Extreme-Scale Computing: Pathways to Convergence - Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry,” The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 435–479, July 2018. DOI: 10.1177/1094342018778123  (1.29 MB)
Aupy, G., A. Benoit, T. Herault, Y. Robert, F. Vivien, and D. Zaidouni, On the Combination of Silent Error Detection and Checkpointing,” UT-CS-13-710: University of Tennessee Computer Science Technical Report, June 2013.  (1.29 MB)
Aupy, G., A. Benoit, T. Herault, Y. Robert, and J. Dongarra, Optimal Checkpointing Period: Time vs. Energy,” University of Tennessee Computer Science Technical Report (also LAWN 281), no. ut-eecs-13-718: University of Tennessee, October 2013.  (440.13 KB)
Aupy, G., A. Gainaru, V. Honoré, P. Raghavan, Y. Robert, and H. Sun, Reservation Strategies for Stochastic Jobs,” 33rd IEEE International Parallel and Distributed Processing Symposium (IPDPS 2019), Rio de Janeiro, Brazil, IEEE Computer Society Press, May 2019.  (808.93 KB)
Aupy, G., M. Faverge, Y. Robert, J. Kurzak, P. Luszczek, and J. Dongarra, Implementing a systolic algorithm for QR factorization on multicore clusters with PaRSEC,” Lawn 277, no. UT-CS-13-709, May 2013.  (298.63 KB)
Aupy, G., and Y. Robert, Scheduling for Fault-Tolerance: An Introduction,” Topics in Parallel and Distributed Computing: Springer International Publishing, pp. 143–170, 2018. DOI: 10.1007/978-3-319-93109-8
Aupy, G., and Y. Robert, Scheduling for fault-tolerance: an introduction,” Innovative Computing Laboratory Technical Report, no. ICL-UT-15-02: University of Tennessee, January 2015.  (416.37 KB)
Aupy, G., A. Benoit, H. Casanova, and Y. Robert, Scheduling Computational Workflows on Failure-prone Platforms,” International Journal of Networking and Computing, vol. 6, no. 1, pp. 2-26, 2016.  (503.81 KB)
Aupy, G., A. Benoit, B. Goglin, L. Pottier, and Y. Robert, Co-Scheduling HPC Workloads on Cache-Partitioned CMP Platforms,” International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1221-1239, November 2019. DOI: 10.1177/1094342019846956  (930.28 KB)
Aupy, G., A. Benoit, S. Dai, L. Pottier, P. Raghavan, Y. Robert, and M. Shantharam, Co-Scheduling Amdhal Applications on Cache-Partitioned Systems,” International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 123–138, January 2018. DOI: 10.1177/1094342017710806  (672.52 KB)
Aupy, G., A. Benoit, B. Goglin, L. Pottier, and Y. Robert, Co-Scheduling HPC Workloads on Cache-Partitioned CMP Platforms,” Cluster 2018, Belfast, UK, IEEE Computer Society Press, September 2018.  (423.75 KB)
Aupy, G., Y. Robert, and F. Vivien, Assuming failure independence: are we right to be wrong?,” The 3rd International Workshop on Fault Tolerant Systems (FTS), Honolulu, Hawaii, IEEE, September 2017.  (597.11 KB)
Aupy, G., A. Benoit, L. Pottier, P. Raghavan, Y. Robert, and M. Shantharam, Co-Scheduling Algorithms for Cache-Partitioned Systems,” 19th Workshop on Advances in Parallel and Distributed Computational Models, Orlando, FL, IEEE Computer Society Press, May 2017. DOI: 10.1109/IPDPSW.2017.60  (584.76 KB)
Ayala, A., S. Tomov, X. Luo, H. Shaiek, A. Haidar, G. Bosilca, and J. Dongarra, Impacts of Multi-GPU MPI Collective Communications on Large FFT Computation,” Workshop on Exascale MPI (ExaMPI) at SC19, Denver, CO, November 2019.  (1.6 MB)
B
Baboulin, M., J. Dongarra, A. Remy, S. Tomov, and I. Yamazaki, Solving Dense Symmetric Indefinite Systems using GPUs,” Concurrency and Computation: Practice and Experience, vol. 29, issue 9, March 2017. DOI: 10.1002/cpe.4055  (1.94 MB)

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