Publications

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Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Department Technical Report, CS-89-85, January 2004.  (6.42 MB)
Dongarra, J., M. Faverge, T. Herault, J. Langou, and Y. Robert, Hierarchical QR Factorization Algorithms for Multi-Core Cluster Systems,” University of Tennessee Computer Science Technical Report (also Lawn 257), no. UT-CS-11-684, October 2011.  (405.71 KB)
Dongarra, J., V. Getov, and K. Walsh, The 30th Anniversary of the Supercomputing Conference: Bringing the Future Closer—Supercomputing History and the Immortality of Now,” Computer, vol. 51, issue 10, pp. 74–85, November 2018.  (1.73 MB)
Dongarra, J., and J. Langou, The Problem with the Linpack Benchmark Matrix Generator,” University of Tennessee Computer Science Technical Report, UT-CS-08-621 (also LAPACK Working Note 206), June 2008.  (136.41 KB)
Dongarra, J., Measuring Computer Performance: A Practioner's Guide,” SIAM Review (book review), vol. 43, no. 2, pp. 383-384, 00 2001.  (558.9 KB)
Dongarra, J., H. Meuer, and E. Strohmaier, Top500 Supercomputer Sites (13th edition),” University of Tennessee Computer Science Department Technical Report, no. UT-CS-99-425, June 1999.  (278.51 KB)
Dongarra, J., P. Beckman, P. Aerts, F. Cappello, T. Lippert, S. Matsuoka, P. Messina, T. Moore, R. Stevens, A. Trefethen, et al., The International Exascale Software Project: A Call to Cooperative Action by the Global High Performance Community,” International Journal of High Performance Computing Applications (to appear), July 2009.  (203.04 KB)
Dongarra, J., and P. Luszczek, HPC Challenge: Design, History, and Implementation Highlights,” On the Road to Exascale Computing: Contemporary Architectures in High Performance Computing (to appear): Chapman & Hall/CRC Press, 00 2012.  (469.92 KB)
Dongarra, J., and P. Luszczek, High Performance Development for High End Computing with Python Language Wrapper (PLW),” International Journal for High Performance Computer Applications, vol. 21, no. 3, pp. 360-369, 00 2007.  (179.32 KB)
Dongarra, J., Report on the TianHe-2A System,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-04: University of Tennessee, September 2017.  (7.15 MB)
Dongarra, J., Z. Chen, G. Bosilca, and J. Langou, Disaster Survival Guide in Petascale Computing: An Algorithmic Approach,” in Petascale Computing: Algorithms and Applications (to appear): Chapman & Hall - CRC Press, 00 2007.  (260.18 KB)
Dongarra, J., M. A. Heroux, and P. Luszczek, HPCG Benchmark: a New Metric for Ranking High Performance Computing Systems,” University of Tennessee Computer Science Technical Report , no. ut-eecs-15-736: University of Tennessee, January 2015.
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, Translational Process: Mathematical Software Perspective,” Journal of Computational Science, September 2020.  (752.59 KB)
Dongarra, J., G. H. Golub, E. Grosse, C. Moler, and K. Moore, Twenty-Plus Years of Netlib and NA-Net,” University of Tennessee Computer Science Department Technical Report, UT-CS-04-526, 00 2006.  (62.79 KB)
Dongarra, J., and D. W. Walker, The Quest for Petascale Computing,” Computing in Science and Engineering, vol. 3, no. 3, pp. 32-39, May 2001.  (178.3 KB)
Dongarra, J., and V. Eijkhout, Self-Adapting Numerical Software and Automatic Tuning of Heuristics,” Lecture Notes in Computer Science, vol. 2660, Melbourne, Australia, Springer Verlag, pp. 759-770, June 2003.  (45.95 KB)
Dongarra, J., A Tribute to Gene Golub,” Computing in Science and Engineering: IEEE, pp. 5, January 2008.
Dongarra, J., S. Hammarling, N. J. Higham, S. Relton, P. Valero-Lara, and M. Zounon, The Design and Performance of Batched BLAS on Modern High-Performance Computing Systems,” International Conference on Computational Science (ICCS 2017), Zürich, Switzerland, Elsevier, June 2017.  (446.14 KB)
Dongarra, J., and A. Geist, Report on the Oak Ridge National Laboratory's Frontier System,” ICL Technical Report, no. ICL-UT-22-05, May 2022.  (16.87 MB)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Department Technical Report, UT-CS-04-526, vol. –89-95, January 2006.  (6.42 MB)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Technical Report, UT-CS-89-85, 00 2010.  (6.42 MB)
Dongarra, J., J. Demmel, P. Husbands, and P. Luszczek, HPCS Library Study Effort,” University of Tennessee Computer Science Technical Report, UT-CS-08-617, January 2008.  (73.22 KB)
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)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software,” University of Tennessee Computer Science Technical Report, no. cs-89-85, February 2013.  (539.24 KB)
Dongarra, J., S. Gottlieb, and W. T. Kramer, Race to Exascale,” Computing in Science and Engineering, vol. 21, issue 1, pp. 4-5, March 2019.  (106.97 KB)
Dongarra, J., and S. Moore, Empirical Performance Tuning of Dense Linear Algebra Software,” in Performance Tuning of Scientific Applications (to appear), 00 2010.
Dongarra, J., D. Laforenza, and S.. Orlando, Recent Advances in Parallel Virtual Machine and Message Passing Interface,” Lecture Notes in Computer Science, vol. 2840: Springer-Verlag, Berlin, January 2003.
Dongarra, J., H. Meuer, and E. Strohmaier, Top500 Supercomputer Sites (15th edition),” University of Tennessee Computer Science Department Technical Report, no. UT-CS-00-442, June 2000.  (278.88 KB)
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.  (568.92 KB)
Dongarra, J., and V. Eijkhout, Self Adapting Numerical Algorithm for Next Generation Applications,” International Journal of High Performance Computing Applications, vol. 17, no. 2, pp. 125-132, January 2003.  (479.18 KB)
Dongarra, J., M. Faverge, T. Herault, J. Langou, and Y. Robert, Hierarchical QR Factorization Algorithms for Multi-Core Cluster Systems,” IPDPS 2012, the 26th IEEE International Parallel and Distributed Processing Symposium, Shanghai, China, IEEE Computer Society Press, May 2012.  (405.71 KB)
Dongarra, J., and et al., Remembering Ken Kennedy,” SciDAC Review, vol. 5, no. 2007, 00 2007.  (519.68 KB)
Dongarra, J., Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Technical Report, no. CS-89-85, 00 2011.  (6.42 MB)
Dongarra, J., Trends in High Performance Computing,” The Computer Journal, vol. 47, no. 4: The British Computer Society, pp. 399-403, 00 2004.  (455.96 KB)
Dongarra, J., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, Accelerating Numerical Dense Linear Algebra Calculations with GPUs,” Numerical Computations with GPUs: Springer International Publishing, pp. 3-28, 2014.  (1.06 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.  (2.53 MB)
Dongarra, J., T. Herault, and Y. Robert, Revisiting the Double Checkpointing Algorithm,” 15th Workshop on Advances in Parallel and Distributed Computational Models, at the IEEE International Parallel & Distributed Processing Symposium, Boston, MA, May 2013.  (591.1 KB)
Dongarra, J., and V. Eijkhout, Numerical Linear Algebra,” Encyclopedia of Computer Science and Technology, eds. Kent, A., Williams, J., vol. 41, pp. 207-233, August 1999.  (262 KB)
Dongarra, J., I. Duff, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Hogg, P. Valero Lara, P. Luszczek, M. Zounon, et al., Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification , July 2018.  (483.05 KB)
Dongarra, J., and P. Luszczek, How Elegant Code Evolves With Hardware: The Case Of Gaussian Elimination,” in Beautiful Code Leading Programmers Explain How They Think: O'Reilly Media, Inc., June 2007.  (257 KB)
Dongarra, J., T. Herault, and Y. Robert, Fault Tolerance Techniques for High-performance Computing,” University of Tennessee Computer Science Technical Report (also LAWN 289), no. UT-EECS-15-734: University of Tennessee, May 2015.
Dongarra, J., K. London, S. Moore, P. Mucci, and D. Terpstra, Using PAPI for Hardware Performance Monitoring on Linux Systems,” Conference on Linux Clusters: The HPC Revolution, Urbana, Illinois, Linux Clusters Institute, June 2001.  (422.35 KB)
Dongarra, J., M. A. Heroux, and P. Luszczek, High Performance Conjugate Gradient Benchmark: A new Metric for Ranking High Performance Computing Systems,” International Journal of High Performance Computing Applications, vol. 30, issue 1, pp. 3 - 10, February 2016.  (277.51 KB)
Dongarra, J., The evolution of mathematical software,” Communications of the ACM, vol. 65227, issue 12, pp. 66 - 72, December 2022.
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, Translational process: Mathematical software perspective,” Journal of Computational Science, vol. 52, pp. 101216, 2021.
Dongarra, J., M. Faverge, Y. Ishikawa, R. Namyst, F. Rue, and F. Trahay, EZTrace: a generic framework for performance analysis,” ICL Technical Report, no. ICL-UT-11-01, December 2010.
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, High Performance Matrix Inversion Based on LU Factorization for Multicore Architectures,” Proceedings of MTAGS11, Seattle, WA, November 2011.  (879.49 KB)
Dongarra, J., Network-Enabled Solvers: A Step Toward Grid-Based Computing,” SIAM News, vol. 34, no. 10, December 2001.
Dongarra, J., and S. Tomov, An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra : NVIDIA Webinar, June 2010.
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, Achieving Numerical Accuracy and High Performance using Recursive Tile LU Factorization,” University of Tennessee Computer Science Technical Report (also as a LAWN), no. ICL-UT-11-08, September 2011.  (618.53 KB)

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