Publications

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Dongarra, J., “LINPACK on Future Manycore and GPu Based Systems,” PARA 2010, Reykjavik, Iceland, June 2010.
Dongarra, J., H. Meuer, H. D. Simon, and E. Strohmaier, “Recent Trends in High Performance Computing,” in Birth of Numerical Analysis (to appear), 00 2009.
Dongarra, J., P. Beckman, T. Moore, P. Aerts, G. Aloisio, J-C. Andre, D. Barkai, J-Y. Berthou, T. Boku, B. Braunschweig, et al., “The International Exascale Software Project Roadmap,” International Journal of High Performance Computing, vol. 25, no. 1, pp. 3-60, January 2011.  (719.74 KB)
Dongarra, J., “The evolution of mathematical software,” Communications of the ACM, vol. 65227, issue 12, pp. 66 - 72, December 2022.
Dongarra, J., H. Meuer, H. D. Simon, and E. Strohmaier, “High Performance Computing Today,” FOMMS 2000: Foundations of Molecular Modeling and Simulation Conference (to appear), January 2000.  (66 KB)
Dongarra, J., G. H. Golub, E. Grosse, C. Moler, and K. Moore, “Netlib and NA-Net: Building a Scientific Computing Community,” IEEE Annals of the History of Computing, vol. 30, no. 2, pp. 30-41, January 2008.  (352.71 KB)
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., J-F. Pineau, Y. Robert, Z. Shi, and F. Vivien, “Revisiting Matrix Product on Master-Worker Platforms,” International Journal of Foundations of Computer Science (IJFCS) (accepted), 00 2007.  (248.66 KB)
Dongarra, J., “Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Technical Report, CS-89-85, January 2008.  (6.42 MB)
Dongarra, J., V. Eijkhout, and P. Luszczek, “Recursive Approach in Sparse Matrix LU Factorization,” Scientific Programming, vol. 9, no. 1, pp. 51-60, 00 2001.  (217.16 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: University of Tennessee, June 2014.  (514.64 KB)
Dongarra, J., V. Eijkhout, and H. van der Vorst, “Iterative Solver Benchmark (LAPACK Working Note 152),” Scientific Programming, vol. 9, no. 4, pp. 223-231, 00 2001.  (168.05 KB)
Dongarra, J., and P. Luszczek, “Reducing the time to tune parallel dense linear algebra routines with partial execution and performance modelling,” University of Tennessee Computer Science Technical Report, no. UT-CS-10-661, October 2010.  (287.87 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 (Chapter 14), pp. 243-282, January 2008.  (257 KB)
Dongarra, J., and P. Luszczek, “HPC Challenge: Design, History, and Implementation Highlights,” Contemporary High Performance Computing: From Petascale Toward Exascale, Boca Raton, FL, Taylor and Francis, 2013.  (790.01 KB)
Dongarra, J., and S. Tomov, An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra : NVIDIA Webinar, June 2010.
Dongarra, J., K. London, S. Moore, P. Mucci, D. Terpstra, H. You, and M. Zhou, “Experiences and Lessons Learned with a Portable Interface to Hardware Performance Counters,” PADTAD Workshop, IPDPS 2003, Nice, France, IEEE, April 2003.  (432.57 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., S. Moore, P. Mucci, K. Seymour, and H. You, “Accurate Cache and TLB Characterization Using Hardware Counters,” International Conference on Computational Science (ICCS 2004), Krakow, Poland, Springer, June 2004.  (167.1 KB)
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, “Exploiting Fine-Grain Parallelism in Recursive LU Factorization,” Proceedings of PARCO'11, no. ICL-UT-11-04, Gent, Belgium, April 2011.
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., 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., T. Herault, and Y. Robert, “Revisiting the Double Checkpointing Algorithm,” University of Tennessee Computer Science Technical Report (LAWN 274), no. ut-cs-13-705, January 2013.  (682.22 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., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, P. Wu, I. Yamazaki, A. YarKhan, M. Abalenkovs, N. Bagherpour, et al., “PLASMA: Parallel Linear Algebra Software for Multicore Using OpenMP,” ACM Transactions on Mathematical Software, vol. 45, issue 2, June 2019.  (7.5 MB)
Dongarra, J., A. Haidar, O. Hernandez, S. Tomov, and M G. Venkata, “POMPEI: Programming with OpenMP4 for Exascale Investigations,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-09: University of Tennessee, December 2017.  (1.1 MB)
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, Y. Jia, K. Kabir, P. Luszczek, and S. Tomov, MAGMA MIC: Linear Algebra Library for Intel Xeon Phi Coprocessors , Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), November 2012.  (6.4 MB)
Dongarra, J., and A. J. van der Steen, “High Performance Computing Systems: Status and Outlook,” Acta Numerica, vol. 21, Cambridge, UK, Cambridge University Press, pp. 379-474, May 2012.  (1.48 MB)
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., and A. Lastovetsky, “An Overview of Heterogeneous High Performance and Grid Computing,” Engineering the Grid (to appear): Nova Science Publishers, Inc., 00 2004.  (199.93 KB)
Dongarra, J., S. Moore, G. D. Peterson, S. Tomov, J. Allred, V. Natoli, and D. Richie, “Exploring New Architectures in Accelerating CFD for Air Force Applications,” Proceedings of the DoD HPCMP User Group Conference, Seattle, Washington, January 2008.  (492.86 KB)
Dongarra, J., J. Kurzak, P. Luszczek, and S. Tomov, “Dense Linear Algebra on Accelerated Multicore Hardware,” High Performance Scientific Computing: Algorithms and Applications, London, UK, Springer-Verlag, 00 2012.
Dongarra, J., H. Meuer, H. D. Simon, and E. Strohmaier, “High Performance Computing Trends,” HERMIS, vol. 2, pp. 155-163, November 2001.
Dongarra, J., “A Not So Simple Matter of Software,” NCSA Access Online: NCSA, 00 2005.  (457.69 KB)
Dongarra, J., “High Performance Computing Trends, Supercomputers, Clusters, and Grids,” Information Processing Society of Japan Symposium Series, vol. 2003, no. 14, pp. 55-58, January 2003.
Dongarra, J., E. Jeannot, E. Saule, and Z. Shi, “Bi-objective Scheduling Algorithms for Optimizing Makespan and Reliability on Heterogeneous Systems,” 19th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA) (submitted), San Diego, CA, June 2007.  (223.82 KB)
Dongarra, J., and P. Beckman, “International Exascale Software Project Roadmap v1.0,” University of Tennessee Computer Science Technical Report, UT-CS-10-654, May 2010.  (719.74 KB)
Dongarra, J., M. Gates, A. Haidar, Y. Jia, K. Kabir, P. Luszczek, and S. Tomov, “Portable HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi,” PPAM 2013, Warsaw, Poland, September 2013.  (284.97 KB)
Dongarra, J., T. Dong, M. Gates, A. Haidar, S. Tomov, and I. Yamazaki, MAGMA: A New Generation of Linear Algebra Library for GPU and Multicore Architectures , Salt Lake City, UT, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC12), Presentation, November 2012.  (4.69 MB)
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., M. A. Heroux, and P. Luszczek, “A New Metric for Ranking High-Performance Computing Systems,” National Science Review, vol. 3, issue 1, pp. 30-35, January 2016.  (393.55 KB)
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., and V. Eijkhout, “Finite-choice Algorithm Optimization in Conjugate Gradients (LAPACK Working Note 159),” University of Tennessee Computer Science Technical Report, UT-CS-03-502, January 2003.  (64.52 KB)
Dongarra, J., G. H. Golub, C. Moler, and K. Moore, “Netlib and NA-Net: building a scientific computing community,” In IEEE Annals of the History of Computing (to appear), August 2007.  (352.71 KB)
Dongarra, J., S. Hammarling, N. J. Higham, S. Relton, and M. Zounon, “Optimized Batched Linear Algebra for Modern Architectures,” Euro-Par 2017, Santiago de Compostela, Spain, Springer, August 2017.  (618.33 KB)
Dongarra, J., P. Luszczek, and A. Petitet, “The LINPACK Benchmark: Past, Present, and Future,” Concurrency: Practice and Experience, vol. 15, pp. 803-820, 00 2008.  (94.86 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)
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.
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, “Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices,” International Conference on Computational Science (ICCS 2017), Zurich, Switzerland, Procedia Computer Science, June 2017.  (364.95 KB)

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