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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., and Y. Robert, “Scheduling for Fault-Tolerance: An Introduction,” Topics in Parallel and Distributed Computing: Springer International Publishing, pp. 143–170, 2018.

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.

(584.76 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.

(930.28 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, 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.

(672.52 KB)

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. 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)

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.

(1.29 MB)

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)

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)

Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., “Integrating Deep Learning in Domain Sciences at Exascale,” 2020 Smoky Mountains Computational Sciences and Engineering Conference (SMC 2020), August 2020.

Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., “Integrating Deep Learning in Domain Sciences at Exascale,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-10: University of Tennessee, August 2020.

(1.09 MB)

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., 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., 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,” Spring Simulation Multi-Conference 2015 (SpringSim'15), Alexandria, VA, SCS, April 2015.

(1.46 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., 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. 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., 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., 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., 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, G. Flegar, and T. Gruetzmacher, “Variable-Size Batched Condition Number Calculation on GPUs,” SBAC-PAD, Lyon, France, September 2018.

(509.3 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., 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., 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., 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., 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., 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)

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