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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)
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, 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)
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., 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., 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, 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, 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,” Cluster 2018, Belfast, UK, IEEE Computer Society Press, September 2018.  (423.75 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., 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., 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)
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)
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)
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., 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., 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., 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., 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, 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)
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)
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)
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. DOI: 10.1145/2712386.2712387  (2.29 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. DOI: 10.1016/j.parco.2017.10.003
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., 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., J. Dongarra, and V. Heuveline, Weighted Block-Asynchronous Relaxation for GPU-Accelerated Systems,” SIAM Journal on Computing (submitted), March 2012.  (811.01 KB)
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. DOI: 10.1007/s11075-016-0110-2  (565.34 KB)
Anzt, H., and J. Dongarra, A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs,” SBAC-PAD, 2018.  (237.68 KB)
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., 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 and Computation: Practice and Experience, vol. 31, no. 6, pp. e4460, March 2019. DOI: 10.1002/cpe.4460  (341.54 KB)
Anzt, H., E. Chow, and J. Dongarra, Iterative Sparse Triangular Solves for Preconditioning,” EuroPar 2015, Vienna, Austria, Springer Berlin, August 2015. DOI: 10.1007/978-3-662-48096-0_50  (322.36 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., 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., , and E. S. Quintana-Ortí, Fine-grained Bit-Flip Protection for Relaxation Methods,” Journal of Computational Science, November 2016. DOI: 10.1016/j.jocs.2016.11.013
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. 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., 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, April 2014.  (578.11 KB)
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., 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., 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., 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., 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., J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, Variable-Size Batched Gauss–Jordan Elimination for Block-Jacobi Preconditioning on Graphics Processors,” Parallel Computing, January 2018. DOI: 10.1016/j.parco.2017.12.006  (1.9 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, June 2017.
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)

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