Publications

Export 932 results:
Filters: Author is Jack Dongarra  [Clear All Filters]
2020
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. DOI: 10.1145/3380930  (5.67 MB)
Farhan, M. Al, A. Abdelfattah, S. Tomov, M. Gates, D. Sukkari, A. Haidar, R. Rosenberg, and J. Dongarra, MAGMA Templates for Scalable Linear Algebra on Emerging Architectures,” The International Journal of High Performance Computing Applications, vol. 34, issue 6, pp. 645-658, November 2020. DOI: 10.1177/1094342020938421
Abdelfattah, A., S. Tomov, and J. Dongarra, Matrix Multiplication on Batches of Small Matrices in Half and Half-Complex Precisions,” Journal of Parallel and Distributed Computing, vol. 145, pp. 188-201, November 2020. DOI: 10.1016/j.jpdc.2020.07.001  (1.3 MB)
Haidar, A., H. Bayraktar, S. Tomov, J. Dongarra, and N. J. Higham, Mixed-Precision Iterative Refinement using Tensor Cores on GPUs to Accelerate Solution of Linear Systems,” Proceedings of the Royal Society A, vol. 476, issue 2243, November 2020. DOI: 10.1098/rspa.2020.0110  (2.24 MB)
Haidar, A., H. Bayraktar, S. Tomov, J. Dongarra, and N. J. Higham, Mixed-Precision Solution of Linear Systems Using Accelerator-Based Computing,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-05: University of Tennessee, May 2020.  (1.03 MB)
Dongarra, J., L. Grigori, and N. J. Higham, Numerical Algorithms for High-Performance Computational Science,” Philosophical Transactions of the Royal Society A, vol. 378, issue 2166, 2020. DOI: 10.1098/rsta.2019.0066  (724.37 KB)
Wyrzykowski, R., E. Deelman, J. Dongarra, and K. Karczewski, Parallel Processing and Applied Mathematics: 13th International Conference, PPAM 2019, Bialystok, Poland, September 8–11, 2019, Revised Selected Papers, Part II,” Lecture Notes in Computer Science, no. 12044: Springer International Publishing, pp. 503, March 2020. DOI: 10.1007/978-3-030-43222-5
Wyrzykowski, R., E. Deelman, J. Dongarra, and K. Karczewski, Parallel Processing and Applied Mathematics: 13th International Conference, PPAM 2019, Bialystok, Poland, September 8–11, 2019, Revised Selected Papers, Part I,” Lecture Notes in Computer Science, 1, no. 12043: Springer International Publishing, pp. 581, March 2020. DOI: 10.1007/978-3-030-43229-4
Dongarra, J., H. Jagode, A. Danalis, D. Barry, and V. Weaver, Performance Application Programming Interface for Extreme-Scale Environments (PAPI-EX) (Poster) , Seattle, WA, 2020 NSF Cyberinfrastructure for Sustained Scientific Innovation (CSSI) Principal Investigator Meeting, 20 2020.  (2.53 MB)
Gates, M., A. Charara, A. YarKhan, D. Sukkari, M. Al Farhan, and J. Dongarra, Performance Tuning SLATE,” SLATE Working Notes, no. 14, ICL-UT-20-01: Innovative Computing Laboratory, University of Tennessee, January 2020.  (1.29 MB)
Luszczek, P., and J. Dongarra, The PLASMA Library on CORAL Systems and Beyond (Poster) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (550.86 KB)
Wong, K., S. Tomov, and J. Dongarra, Project-Based Research and Training in High Performance Data Sciences, Data Analytics, and Machine Learning,” The Journal of Computational Science Education, vol. 11, issue 1, pp. 36-44, January 2020. DOI: 10.22369/issn.2153-4136/11/1/7  (4.4 MB)
Demmel, J., J. Dongarra, J. Langou, J. Langou, P. Luszczek, and M. Mahoney, Prospectus for the Next LAPACK and ScaLAPACK Libraries: Basic ALgebra LIbraries for Sustainable Technology with Interdisciplinary Collaboration (BALLISTIC),” LAPACK Working Notes, no. 297, ICL-UT-20-07: University of Tennessee.  (1.41 MB)
Lu, Y., I. Yamazaki, F. Ino, Y. Matsushita, S. Tomov, and J. Dongarra, Reducing the Amount of out-of-core Data Access for GPU-Accelerated Randomized SVD,” Concurrency and Computation: Practice and Experience, April 2020. DOI: 10.1002/cpe.5754  (1.43 MB)
Lindquist, N., P. Luszczek, and J. Dongarra, Replacing Pivoting in Distributed Gaussian Elimination with Randomized Techniques,” 2020 IEEE/ACM 11th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), Atlanta, GA, IEEE, November 2020.  (184.6 KB)
Dongarra, J., Report on the Fujitsu Fugaku System,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-06: University of Tennessee, June 2020.  (3.3 MB)
Luszczek, P., Y. Tsai, N. Lindquist, H. Anzt, and J. Dongarra, Scalable Data Generation for Evaluating Mixed-Precision Solvers,” 2020 IEEE High Performance Extreme Computing Conference (HPEC): IEEE, September 2020.
Abdelfattah, A., T. Costa, J. Dongarra, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Kurzak, P. Luszczek, S. Tomov, et al., A Set of Batched Basic Linear Algebra Subprograms,” ACM Transactions on Mathematical Software, October 2020.
YarKhan, A., M. Al Farhan, D. Sukkari, M. Gates, and J. Dongarra, SLATE Performance Report: Updates to Cholesky and LU Factorizations,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-14: University of Tennessee, October 2020.  (1.64 MB)
Gates, M., A. Charara, J. Kurzak, A. YarKhan, M. Al Farhan, D. Sukkari, and J. Dongarra, SLATE: Software for Linear Algebra Targeting Exascale (POSTER) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (546.56 KB)
Gates, M., J. Kurzak, A. YarKhan, A. Charara, J. Finney, D. Sukkari, M. Al Farhan, I. Yamazaki, P. Wu, and J. Dongarra, SLATE Tutorial , Houston, TX, 2020 ECP Annual Meeting, February 2020.  (12.14 MB)
Gates, M., A. Charara, J. Kurzak, A. YarKhan, M. Al Farhan, D. Sukkari, and J. Dongarra, SLATE Users' Guide,” SLATE Working Notes, no. 10, ICL-UT-19-01: Innovative Computing Laboratory, University of Tennessee, July 2020.  (2.35 MB)
Abdelfattah, A., H. Anzt, E. Boman, E. Carson, T. Cojean, J. Dongarra, M. Gates, T. Gruetzmacher, N. J. Higham, S. Li, et al., A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic,” SLATE Working Notes, no. 15, ICL-UT-20-08: University of Tennessee, July 2020.  (3.98 MB)
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, Translational Process: Mathematical Software Perspective,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-11, August 2020.  (752.59 KB)
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, Translational Process: Mathematical Software Perspective,” Journal of Computational Science, September 2020. DOI: 10.1016/j.jocs.2020.101216  (752.59 KB)
Krzhizhanovskaya, V., G. Závodszky, M. Lees, J. Dongarra, P. Sloot, S. Brissos, and J. Teixeira, Twenty Years of Computational Science,” International Conference on Computational Science (ICCS 2020), Amsterdam, Netherlands, June 2020.  (149.66 KB)
Zhong, D., Q. Cao, G. Bosilca, and J. Dongarra, Using Advanced Vector Extensions AVX-512 for MPI Reduction,” EuroMPI/USA '20: 27th European MPI Users' Group Meeting, Austin, TX, September 2020. DOI: 10.1145/3416315.3416316  (634.45 KB)
Zhong, D., G. Bosilca, Q. Cao, and J. Dongarra, Using Advanced Vector Extensions AVX-512 for MPI Reduction (Poster) , Austin, TX, EuroMPI/USA '20: 27th European MPI Users' Group Meeting, September 2020.  (708.68 KB)
Zhong, D., P. Shamis, Q. Cao, G. Bosilca, and J. Dongarra, Using Arm Scalable Vector Extension to Optimize Open MPI,” 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID 2020), Melbourne, Australia, IEEE/ACM, May 2020. DOI: 10.1109/CCGrid49817.2020.00-71  (359.95 KB)
Tsai, Y., P. Luszczek, and J. Dongarra, Using Quantized Integer in LU Factorization with Partial Pivoting (Poster) , Seattle, WA, SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP20), February 2020.  (6.65 MB)
2021
Herault, T., Y. Robert, G. Bosilca, R. Harrison, C. Lewis, E. Valeev, and J. Dongarra, Distributed-Memory Multi-GPU Block-Sparse Tensor Contraction for Electronic Structure,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.
Cao, Q., Y. Pei, K. Akbudak, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, Leveraging PaRSEC Runtime Support to Tackle Challenging 3D Data-Sparse Matrix Problems,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.  (1.08 MB)

Pages