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Journal Article

Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, M. Baboulin, J. Falcou, and J. Dongarra, “Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices,” Parallel Computing, vol. 81, pp. 1–21, January 2019.

(3.27 MB)

Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, “Analysis and Design Techniques towards High-Performance and Energy-Efficient Dense Linear Solvers on GPUs,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 12, pp. 2700–2712, December 2018.

(2.53 MB)

Seo, S., A. Amer, P. Balaji, C. Bordage, G. Bosilca, A. Brooks, P. Carns, A. Castello, D. Genet, T. Herault, et al., “Argobots: A Lightweight Low-Level Threading and Tasking Framework,” IEEE Transactions on Parallel and Distributed Systems, October 2017.

Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, “Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures,” Journal of Computational Science, vol. 26, pp. 226–236, May 2018.

(3.73 MB)

Luszczek, P., A. Abdelfattah, H. Anzt, A. Suzuki, and S. Tomov, “Batched sparse and mixed-precision linear algebra interface for efficient use of GPU hardware accelerators in scientific applications,” Future Generation Computer Systems, vol. 160, pp. 359 - 374, November 2024.

Luszczek, P., A. Abdelfattah, H. Anzt, A. Suzuki, and S. Tomov, “Batched sparse and mixed-precision linear algebra interface for efficient use of GPU hardware accelerators in scientific applications,” Future Generation Computer Systems, vol. 160, pp. 359 - 374, November 2024.

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)

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., 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., 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)

Herault, T., Y. Robert, A. Bouteiller, D. Arnold, K. Ferreira, G. Bosilca, and J. Dongarra, “Checkpointing Strategies for Shared High-Performance Computing Platforms,” International Journal of Networking and Computing, vol. 9, no. 1, pp. 28–52, 2019.

(490.5 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)

Aliaga, J. I., H. Anzt, T. Grützmacher, E. S. Quintana-Ortí, and A. E. Thomas, “Compressed basis GMRES on high-performance graphics processing units,” The International Journal of High Performance Computing Applications, May 2022.

(13.52 MB)

Aliaga, J. I., H. Anzt, T. Grützmacher, E. S. Quintana-Ortí, and A. E. Thomas, “Compressed basis GMRES on high-performance graphics processing units,” The International Journal of High Performance Computing Applications, May 2022.

(13.52 MB)

Aliaga, J. I., H. Anzt, T. Grützmacher, E. S. Quintana-Orti, and A. E. Thomas, “Compression and load balancing for efficient sparse matrix‐vector product on multicore processors and graphics processing units,” Concurrency and Computation: Practice and Experience, vol. 34, issue 14, June 2022.

(749.82 KB)

Aliaga, J. I., H. Anzt, T. Grützmacher, E. S. Quintana-Orti, and A. E. Thomas, “Compression and load balancing for efficient sparse matrix‐vector product on multicore processors and graphics processing units,” Concurrency and Computation: Practice and Experience, vol. 34, issue 14, June 2022.

(749.82 KB)

Sloot, P. M., D. Abramson, A. V. Bogdanov, J. Dongarra, A. Zomaya, and Y. Gorbachev, “Computational Science — ICCS 2003,” Lecture Notes in Computer Science, vol. 2657-2660, ICCS 2003, International Conference. Melbourne, Australia, Springer-Verlag, Berlin, June 2003.

“Computational Science – ICCS 2009, Proceedings of the 9th International Conference,” Lecture Notes in Computer Science: Theoretical Computer Science and General Issues, vol. -, no. 5544-5545, Baton Rouge, LA, May 2009.

“Computational Science – ICCS 2009, Proceedings of the 9th International Conference,” Lecture Notes in Computer Science: Theoretical Computer Science and General Issues, vol. -, no. 5544-5545, Baton Rouge, LA, May 2009.

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)

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, 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)

Agarwal, P., R. A.. Alexander, E.. Apra, S. Balay, A. S. Bland, J. Colgan, E. D'Azevedo, J. Dongarra, T. Dunigan, M. Fahey, et al., “Cray X1 Evaluation Status Report,” Oak Ridge National Laboratory Report, vol. /-2004/13, January 2004.

(817.33 KB)

Agarwal, P., R. A.. Alexander, E.. Apra, S. Balay, A. S. Bland, J. Colgan, E. D'Azevedo, J. Dongarra, T. Dunigan, M. Fahey, et al., “Cray X1 Evaluation Status Report,” Oak Ridge National Laboratory Report, vol. /-2004/13, January 2004.

(817.33 KB)

Agarwal, P., R. A.. Alexander, E.. Apra, S. Balay, A. S. Bland, J. Colgan, E. D'Azevedo, J. Dongarra, T. Dunigan, M. Fahey, et al., “Cray X1 Evaluation Status Report,” Oak Ridge National Laboratory Report, vol. /-2004/13, January 2004.

(817.33 KB)

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, January 2019.

Dongarra, J., R. Graybill, W. Harrod, R. Lucas, E. Lusk, P. Luszczek, J. McMahon, A. Snavely, J. Vetter, K. Yelick, et al., “DARPA's HPCS Program: History, Models, Tools, Languages,” in Advances in Computers, vol. 72: Elsevier, January 2008.

(3.61 MB)

Pjesivac–Grbovic, J., G. Bosilca, G. Fagg, T. Angskun, and J. Dongarra, “Decision Trees and MPI Collective Algorithm Selection Problem,” Euro-Par 2007, Rennes, France, Springer, pp. 105–115, August 2007.

(552.94 KB)

Kolev, T., P. Fischer, M. Min, J. Dongarra, J. Brown, V. Dobrev, T. Warburton, S. Tomov, M. S. Shephard, A. Abdelfattah, et al., “Efficient exascale discretizations: High-order finite element methods,” The International Journal of High Performance Computing Applications, pp. 10943420211020803, 2021.

Hiroyasu, T., M. Miki, S. Ogura, K. Aoi, T. Yoshida, Y. Okamoto, and J. Dongarra, “Energy Minimization of Protein Tertiary Structure by Parallel Simulated Annealing using Genetic Crossover,” Special Issue on Biological Applications of Genetic and Evolutionary Computation (submitted), March 2003.

(438.68 KB)

Hadri, B., H. Ltaeif, E. Agullo, and J. Dongarra, “Enhancing Parallelism of Tile QR Factorization for Multicore Architectures,” Submitted to Transaction on Parallel and Distributed Systems, December 2009.

(464.23 KB)

Nayak, P., T. Cojean, and H. Anzt, “Evaluating Asynchronous Schwarz Solvers on GPUs,” International Journal of High Performance Computing Applications, August 2020.

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., 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.

(1.98 MB)

Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, “Factorization and Inversion of a Million Matrices using GPUs: Challenges and Countermeasures,” Procedia Computer Science, vol. 108, pp. 606–615, June 2017.

(643.44 KB)

Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, “Fast Cholesky Factorization on GPUs for Batch and Native Modes in MAGMA,” Journal of Computational Science, vol. 20, pp. 85–93, May 2017.

(3.6 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)

Fagg, G., J. Pjesivac–Grbovic, G. Bosilca, T. Angskun, and J. Dongarra, “Flexible collective communication tuning architecture applied to Open MPI,” 2006 Euro PVM/MPI (submitted), Bonn, Germany, January 2006.

(206.58 KB)

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., 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)

Cojean, T., Y-H. Mike Tsai, and H. Anzt, “Ginkgo—A math library designed for platform portability,” Parallel Computing, vol. 111, pp. 102902, February 2022.

Abdelfattah, A., V. Barra, N. Beams, R. Bleile, J. Brown, J-S. Camier, R. Carson, N. Chalmers, V. Dobrev, Y. Dudouit, et al., “GPU algorithms for Efficient Exascale Discretizations,” Parallel Computing, vol. 108, pp. 102841, 2021.

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)

Haidar, A., A. Abdelfattah, M. Zounon, S. Tomov, and J. Dongarra, “A Guide for Achieving High Performance with Very Small Matrices on GPUs: A Case Study of Batched LU and Cholesky Factorizations,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 5, pp. 973–984, May 2018.

(832.92 KB)

Palma, J., J. Dongarra, and V. Hernández, “High Performance Computing for Computational Science,” Lecture Notes in Computer Science, vol. 2565, VECPAR 2002, 5th International Conference June 26-28, 2002, Springer-Verlag, Berlin, January 2003.

Caniou, Y., E. Caron, F. Desprez, H. Nakada, Y. Tanaka, and K. Seymour, “High Performance GridRPC Middleware,” Recent developments in Grid Technology and Applications: Nova Science Publishers, 00 2008.

(923.06 KB)

Agullo, E., C. Augonnet, J. Dongarra, H. Ltaeif, R. Namyst, S. Thibault, and S. Tomov, “A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs,” in GPU Computing Gems, Jade Edition, vol. 2: Elsevier, pp. 473-484, 00 2011.

Agullo, E., C. Augonnet, J. Dongarra, H. Ltaeif, R. Namyst, S. Thibault, and S. Tomov, “A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs,” in GPU Computing Gems, Jade Edition, vol. 2: Elsevier, pp. 473-484, 00 2011.

Alam, S., R. F. Barrett, H. Jagode, J. A.. Kuehn, S. W. Poole, and R.. Sankaran, “Impact of Quad-core Cray XT4 System and Software Stack on Scientific Computation,” Euro-Par 2009, Lecture Notes in Computer Science, vol. 5704/2009, Delft, The Netherlands, Springer Berlin / Heidelberg, pp. 334-344, August 2009.

(312.74 KB)

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, November 2015.

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