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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., 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. Fagg, R. Hempel, and D. W. Walker, Message Passing Software Systems,” Encyclopedia of Electrical and Engineering, Supplement 1: John Wiley & Sons, Inc., 00 2000.  (289.38 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. DOI: 10.1093/nsr/nwv084  (393.55 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., 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., 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., 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, 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  (2.5 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, no. CS-89-85, 00 2011.  (6.42 MB)
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., M. Faverge, H. Ltaeif, and P. Luszczek, Achieving numerical accuracy and high performance using recursive tile LU factorization with partial pivoting,” Concurrency and Computation: Practice and Experience, vol. 26, issue 7, pp. 1408-1431, May 2014. DOI: 10.1002/cpe.3110  (1.96 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., I. Duff, D. Sorensen, and H. van der Vorst, Numerical Linear Algebra for High-Performance Computers,” Software, Environments and Tools: SIAM, 1998. DOI: 10.1137/1.9780898719611
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., 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., High Performance Computing Trends and Self Adapting Numerial Software,” Lecture Notes in Computer Science, High Performance Computing, 5th International Symposium ISHPC, vol. 2858, Tokyo-Odaiba, Japan, Springer-Verlag, Heidelberg, pp. 1-9, January 2003.
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.

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