Publications

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Danalis, A., G. Bosilca, A. Bouteiller, T. Herault, and J. Dongarra, “PTG: An Abstraction for Unhindered Parallelism,” International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing (WOLFHPC), New Orleans, LA, IEEE Press, November 2014.  (480.05 KB)
Davis, J., T. Gao, S. Chandrasekaran, H. Jagode, A. Danalis, P. Balaji, J. Dongarra, and M. Taufer, “Characterization of Power Usage and Performance in Data-Intensive Applications using MapReduce over MPI,” 2019 International Conference on Parallel Computing (ParCo2019), Prague, Czech Republic, September 2019.
Demmel, J., J. Dongarra, V. Eijkhout, E. Fuentes, A. Petitet, R. Vuduc, C. Whaley, and K. Yelick, “Self Adapting Linear Algebra Algorithms and Software,” IEEE Proceedings (to appear), 00 2004.  (587.67 KB)
Demmel, J., J. Dongarra, A. Fox, S. Williams, V. Volkov, and K. Yelick, “Accelerating Time-To-Solution for Computational Science and Engineering,” SciDAC Review, 00 2009.  (739.11 KB)
Demmel, J., J. Dongarra, J. Langou, J. Langou, P. Luszczek, and M. Mahoney, “Prospectus for the Next LAPACK and ScaLAPACK Libraries: Basic ALgebra LIbraries for Sustainable Technology with Interdisciplinary Collaboration (BALLISTIC),” LAPACK Working Notes, no. 297, ICL-UT-20-07: University of Tennessee.  (1.41 MB)
Demmel, J., J. Dongarra, B.. Parlett, W. Kahan, M. Gu, D. Bindel, Y. Hida, X. Li, O. Marques, J. E. Riedy, et al., “Prospectus for the Next LAPACK and ScaLAPACK Libraries,” PARA 2006, Umea, Sweden, June 2006.  (460.11 KB)
Demmel, J., and J. Dongarra, LAPACK 2005 Prospectus: Reliable and Scalable Software for Linear Algebra Computations on High End Computers : LAPACK Working Note 164, January 2005.  (172.59 KB)
Dempsey, B., and D. Weiss, “Towards An Efficient, Scalable Replication Mechanism for the I2-DSI Project,” University of North Carolina School of Library and Information Science Technical Report, no. TR-1999-01, January 1999.
Deshmukh, S., R. Yokota, and G. Bosilca, “Cache Optimization and Performance Modeling of Batched, Small, and Rectangular Matrix Multiplication on Intel, AMD, and Fujitsu Processors,” ACM Transactions on Mathematical Software, vol. 49, issue 3, pp. 1 - 29, September 2023.
Deshmukh, S., R. Yokota, G. Bosilca, and Q. Ma, “O(N) distributed direct factorization of structured dense matrices using runtime systems,” 52nd International Conference on Parallel Processing (ICPP 2023), Salt Lake City, Utah, ACM, August 2023.
Dewolfs, D., J. Broeckhove, V. Sunderam, and G. Fagg, “FT-MPI, Fault-Tolerant Metacomputing and Generic Name Services: A Case Study,” Lecture Notes in Computer Science, vol. 4192, no. ICL-UT-06-14: Springer Berlin / Heidelberg, pp. 133-140, 00 2006.  (362.44 KB)
Donfack, S., S. Tomov, and J. Dongarra, “Performance evaluation of LU factorization through hardware counter measurements,” University of Tennessee Computer Science Technical Report, no. ut-cs-12-700, October 2012.  (794.82 KB)
Donfack, S., J. Dongarra, M. Faverge, M. Gates, J. Kurzak, P. Luszczek, and I. Yamazaki, “A Survey of Recent Developments in Parallel Implementations of Gaussian Elimination,” Concurrency and Computation: Practice and Experience, vol. 27, issue 5, pp. 1292-1309, April 2015.  (783.45 KB)
Donfack, S., S. Tomov, and J. Dongarra, “Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” University of Tennessee Computer Science Technical Report, no. ut-cs-13-713, July 2013.  (659.77 KB)
Donfack, S., S. Tomov, and J. Dongarra, “Dynamically balanced synchronization-avoiding LU factorization with multicore and GPUs,” Fourth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), IPDPS 2014, May 2014.  (490.08 KB)
Donfack, S., J. Dongarra, M. Faverge, M. Gates, J. Kurzak, P. Luszczek, and I. Yamazaki, “On Algorithmic Variants of Parallel Gaussian Elimination: Comparison of Implementations in Terms of Performance and Numerical Properties,” University of Tennessee Computer Science Technical Report, no. UT-CS-13-715, July 2013, 2012.  (358.98 KB)
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)
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)
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, “Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices using GPUs,” Journal of Computational Science, vol. 26, pp. 237–245, May 2018.  (2.18 MB)
Dong, T., A. Haidar, S. Tomov, and J. Dongarra, “A Fast Batched Cholesky Factorization on a GPU,” International Conference on Parallel Processing (ICPP-2014), Minneapolis, MN, September 2014.  (1.37 MB)
Dong, T., V. Dobrev, T. Kolev, R. Rieben, S. Tomov, and J. Dongarra, “Hydrodynamic Computation with Hybrid Programming on CPU-GPU Clusters,” University of Tennessee Computer Science Technical Report, no. ut-cs-13-714, July 2013.  (866.68 KB)
Dong, T., T. Kolev, R. Rieben, V. Dobrev, S. Tomov, and J. Dongarra, “Acceleration of the BLAST Hydro Code on GPU,” Supercomputing '12 (poster), Salt Lake City, Utah, SC12, November 2012.
Dong, T., A. Haidar, P. Luszczek, J. Harris, S. Tomov, and J. Dongarra, “LU Factorization of Small Matrices: Accelerating Batched DGETRF on the GPU,” 16th IEEE International Conference on High Performance Computing and Communications (HPCC), Paris, France, IEEE, August 2014.  (684.73 KB)
Dong, T., A. Haidar, P. Luszczek, S. Tomov, A. Abdelfattah, and J. Dongarra, “MAGMA Batched: A Batched BLAS Approach for Small Matrix Factorizations and Applications on GPUs,” Innovative Computing Laboratory Technical Report, no. ICL-UT-16-02: University of Tennessee, August 2016.  (929.79 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., “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., 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., L. Grigori, and N. J. Higham, “Numerical Algorithms for High-Performance Computational Science,” Philosophical Transactions of the Royal Society A, vol. 378, issue 2166, 2020.  (724.37 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., J. Demmel, J. Langou, and J. Langou, “2016 Dense Linear Algebra Software Packages Survey,” University of Tennessee Computer Science Technical Report, no. UT-EECS-16-744 / LAWN 290: University of Tennessee, September 2016.  (366.43 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.
Dongarra, J., V. Eijkhout, and P. Luszczek, “Recursive approach in sparse matrix LU factorization,” Proceedings of 1st SGI Users Conference, Cracow, Poland (ACC Cyfronet UMM, 2000), pp. 409-418, January 2000.  (176.14 KB)
Dongarra, J., and P. Luszczek, “Introduction to the HPCChallenge Benchmark Suite,” ICL Technical Report, no. ICL-UT-05-01, January 2005.  (124.86 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. 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., A. D. Malony, S. Moore, P. Mucci, and S. Shende, “Performance Instrumentation and Measurement for Terascale Systems,” ICCS 2003 Terascale Workshop, Melbourne, Australia, Springer, Berlin, Heidelberg, June 2003.  (5.36 MB)
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., “Sunway TaihuLight Supercomputer Makes Its Appearance,” National Science Review, vol. 3, issue 3, pp. 256-266, September 2016.  (292.11 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.  (2.5 MB)
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., “LINPACK on Future Manycore and GPu Based Systems,” PARA 2010, Reykjavik, Iceland, June 2010.
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., 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., 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., H. Meuer, H. D. Simon, and E. Strohmaier, “Biannual Top-500 Computer Lists Track Changing Environments for Scientific Computing,” SIAM News, vol. 34, no. 9, October 2002.  (2.62 MB)
Dongarra, J., and P. Raghavan, “A New Recursive Implementation of Sparse Cholesky Factorization,” Proceedings of 16th IMACS World Congress 2000 on Scientific Computing, Applications Mathematics and Simulation, Lausanne, Switzerland, August 2000.

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