Publications

Export 1296 results:
Journal Article
Baboulin, M., J. Dongarra, J. Herrmann, and S. Tomov, “Accelerating Linear System Solutions Using Randomization Techniques,” ACM Transactions on Mathematical Software (also LAWN 246), vol. 39, issue 2, February 2013. DOI: 10.1145/2427023.2427025  (358.79 KB)
Jagode, H., A. Danalis, and J. Dongarra, “Accelerating NWChem Coupled Cluster through dataflow-based Execution,” The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 540--551, July 2018. DOI: 10.1177/1094342016672543  (1.68 MB)
Jagode, H., A. Danalis, and J. Dongarra, “Accelerating NWChem Coupled Cluster through Dataflow-Based Execution,” The International Journal of High Performance Computing Applications, pp. 1–13, January 2017. DOI: 10.1177/1094342016672543  (4.07 MB)
Lindquist, N., P. Luszczek, and J. Dongarra, “Accelerating Restarted GMRES with Mixed Precision Arithmetic,” IEEE Transactions on Parallel and Distributed Systems, June 2021. DOI: 10.1109/TPDS.2021.3090757  (572.4 KB)
Baboulin, M., A. Buttari, J. Dongarra, J. Kurzak, J. Langou, J. Langou, P. Luszczek, and S. Tomov, “Accelerating Scientific Computations with Mixed Precision Algorithms,” Computer Physics Communications, vol. 180, issue 12, pp. 2526-2533, December 2009. DOI: 10.1016/j.cpc.2008.11.005  (402.69 KB)
Tomov, S., R. Nath, and J. Dongarra, “Accelerating the Reduction to Upper Hessenberg, Tridiagonal, and Bidiagonal Forms through Hybrid GPU-Based Computing,” Parallel Computing, vol. 36, no. 12, pp. 645-654, 00 2010.  (1.39 MB)
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, “Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices using GPUs,” Journal of Computational Science, vol. 26, pp. 237–245, May 2018. DOI: 10.1016/j.jocs.2018.01.007  (2.18 MB)
Gates, M., S. Tomov, and J. Dongarra, “Accelerating the SVD Two Stage Bidiagonal Reduction and Divide and Conquer Using GPUs,” Parallel Computing, vol. 74, pp. 3–18, May 2018. DOI: 10.1016/j.parco.2017.10.004  (1.34 MB)
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, “Achieving numerical accuracy and high performance using recursive tile LU factorization with partial pivoting,” Concurrency and Computation: Practice and Experience, vol. 26, issue 7, pp. 1408-1431, May 2014. DOI: 10.1002/cpe.3110  (1.96 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. DOI: 10.1002/cpe.4460  (341.54 KB)
Jagode, H., A. Danalis, G. Congiu, D. Barry, A. Castaldo, and J. Dongarra, “Advancements of PAPI for the exascale generation,” The International Journal of High Performance Computing Applications, December 2024. DOI: 10.1177/10943420241303884
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. DOI: 10.1016/j.parco.2018.10.003  (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. DOI: 10.1109/TPDS.2018.2842785  (2.53 MB)
Haidar, A., H. Ltaeif, A. YarKhan, and J. Dongarra, “Analysis of Dynamically Scheduled Tile Algorithms for Dense Linear Algebra on Multicore Architectures,” Submitted to Concurrency and Computations: Practice and Experience, November 2010.  (1.65 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. DOI: 10.1109/TPDS.2017.2766062
Dongarra, J., N. Emad, and S. Abolfazl Shahzadeh-Fazeli, “An Asynchronous Algorithm on NetSolve Global Computing System,” Future Generation Computer Systems, vol. 22, issue 3, pp. 279-290, February 2006. DOI: 10.1016/j.future.2005.10.003  (568.92 KB)
Kurzak, J., S. Tomov, and J. Dongarra, “Autotuning GEMM Kernels for the Fermi GPU,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 11, November 2012. DOI: 10.1109/TPDS.2011.311  (742.5 KB)
Balaprakash, P., J. Dongarra, T. Gamblin, M. Hall, J. Hollingsworth, B. Norris, and R. Vuduc, “Autotuning in High-Performance Computing Applications,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2068–2083, November 2018. DOI: 10.1109/JPROC.2018.2841200  (2.5 MB)
Dongarra, J., M. Gates, J. Kurzak, P. Luszczek, and Y. Tsai, “Autotuning Numerical Dense Linear Algebra for Batched Computation With GPU Hardware Accelerators,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2040–2055, November 2018. DOI: 10.1109/JPROC.2018.2868961  (2.53 MB)
Luszczek, P., J. Kurzak, I. Yamazaki, D. Keffer, V. Maroulas, and J. Dongarra, “Autotuning Techniques for Performance-Portable Point Set Registration in 3D,” Supercomputing Frontiers and Innovations, vol. 5, no. 4, December 2018. DOI: 10.14529/jsfi180404  (720.15 KB)
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. DOI: 10.1016/j.jocs.2018.01.005  (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. DOI: 10.1016/j.future.2024.06.004

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