Publications

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Dongarra, J., and et al., Remembering Ken Kennedy,” SciDAC Review, vol. 5, no. 2007, 00 2007.  (519.68 KB)
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., 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., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, The Singular Value Decomposition: Anatomy of Optimizing an Algorithm for Extreme Scale,” SIAM Review, vol. 60, issue 4, pp. 808–865, November 2018. DOI: 10.1137/17M1117732
Dongarra, J., H. Meuer, H. D. Simon, and E. Strohmaier, High Performance Computing Trends,” HERMIS, vol. 2, pp. 155-163, November 2001.
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., A Not So Simple Matter of Software,” NCSA Access Online: NCSA, 00 2005.  (457.69 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., 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., 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., and S. Moore, Empirical Performance Tuning of Dense Linear Algebra Software,” in Performance Tuning of Scientific Applications (to appear), 00 2010.
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., 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., 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., 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., 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 S. Tomov, An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra : NVIDIA Webinar, June 2010.
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., 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., 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. DOI: 10.1007/978-3-319-06548-9_1  (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. DOI: 10.1109/JPROC.2018.2868961
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., 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., 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)
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. 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., 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., 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. DOI: DOI:10.1016/j.procs.2017.05.138
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., 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., 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., G. Bosilca, R. Delmas, and J. Langou, Algorithmic Based Fault Tolerance Applied to High Performance Computing,” Journal of Parallel and Distributed Computing, vol. 69, pp. 410-416, 00 2009.  (313.55 KB)
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)
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), vol. 19, no. 6, pp. 1317-1336, December 2008.  (248.66 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., 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., Performance of Various Computers Using Standard Linear Equations Software (Linpack Benchmark Report),” University of Tennessee Computer Science Dept. Technical Report CS-89-85, 00 2007.  (6.42 MB)
Dongarra, J., LINPACK on Future Manycore and GPu Based Systems,” PARA 2010, Reykjavik, Iceland, June 2010.
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. DOI: 10.1177/1094342015593158  (277.51 KB)
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., J-F. Pineau, Y. Robert, and F. Vivien, Matrix Product on Heterogeneous Master Worker Platforms,” 2008 PPoPP Conference, Salt Lake City, Utah, January 2008.
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., P. Beckman, and et al., The International Exascale Software Project Roadmap,” International Journal of High Performance Computing, vol. 25, no. 1, pp. 3-60, 00 2011.  (719.74 KB)
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., 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., 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., 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 (to appear), 2019.  (7.5 MB)
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)

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