Publications

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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., and S. Moore, Empirical Performance Tuning of Dense Linear Algebra Software,” in Performance Tuning of Scientific Applications (to appear), 00 2010.
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., Report on the Sunway TaihuLight System,” University of Tennessee Computer Science Technical Report, no. UT-EECS-16-742: University of Tennessee, June 2016.
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., 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., M. Gates, P. Luszczek, and S. Tomov, Translational Process: Mathematical Software Perspective,” Journal of Computational Science, September 2020.  (752.59 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., 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., 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., 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., J. Kurzak, P. Luszczek, and I. Yamazaki, PULSAR Users’ Guide, Parallel Ultra-Light Systolic Array Runtime,” University of Tennessee EECS Technical Report, no. UT-EECS-14-733: University of Tennessee, November 2014.  (561.56 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., 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., M. A. Heroux, and P. Luszczek, High-Performance Conjugate-Gradient Benchmark: A New Metric for Ranking High-Performance Computing Systems,” The International Journal of High Performance Computing Applications, 2015.  (336.19 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., 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 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., 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., 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., A Not So Simple Matter of Software,” NCSA Access Online: NCSA, 00 2005.  (457.69 KB)
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., H. Meuer, H. D. Simon, and E. Strohmaier, High Performance Computing Trends,” HERMIS, vol. 2, pp. 155-163, November 2001.
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., 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., 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., 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., 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., A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and A. YarKhan, Model-Driven One-Sided Factorizations on Multicore, Accelerated Systems,” Supercomputing Frontiers and Innovations, vol. 1, issue 1, 2014.  (1.86 MB)
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., 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., 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., 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., 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., 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., The HPL Benchmark: Past, Present & Future , ISC High Performance, Frankfurt, Germany, July 2016.  (3.41 MB)
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., P. Kacsuk, and N.. Podhorszki, Recent Advances in Parallel Virtual Machine and Message Passing Interface,” Lecture Notes in Computer Science: Proceedings of 7th European PVM/MPI Users' Group Meeting 2000, (Hungary: Springer Verlag), pp. V1908, January 2000.
Dongarra, J., LINPACK on Future Manycore and GPu Based Systems,” PARA 2010, Reykjavik, Iceland, June 2010.
Dongarra, J., N. J. Higham, M. R. Dennis, P. Glendinning, P. A. Martin, F. Santosa, and J. Tanner, High-Performance Computing,” The Princeton Companion to Applied Mathematics, Princeton, New Jersey, Princeton University Press, pp. 839-842, 2015.
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., 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., 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., 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., S. Moore, and A. Trefethen, Numerical Libraries and Tools for Scalable Parallel Cluster Computing,” International Journal of High Performance Applications and Supercomputing, vol. 15, no. 2, pp. 175-180, January 2001.  (37.38 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., M. Gates, P. Luszczek, and S. Tomov, Translational process: Mathematical software perspective,” Journal of Computational Science, vol. 52, pp. 101216, 2021.
Dongarra, J., T. Herault, and Y. Robert, Performance and Reliability Trade-offs for the Double Checkpointing Algorithm,” International Journal of Networking and Computing, vol. 4, no. 1, pp. 32-41.  (859.04 KB)
Dong, T., V. Dobrev, T. Kolev, R. Rieben, S. Tomov, and J. Dongarra, A Step towards Energy Efficient Computing: Redesigning A Hydrodynamic Application on CPU-GPU,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.01 MB)

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