Publications

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Danalis, A., H. Jagode, and J. Dongarra, Does your tool support PAPI SDEs yet? , Tahoe City, CA, 13th Scalable Tools Workshop, July 2019.  (3.09 MB)
Danalis, A., P. Luszczek, G. Marin, J. Vetter, and J. Dongarra, “BlackjackBench: Hardware Characterization with Portable Micro-Benchmarks and Automatic Statistical Analysis of Results,” IEEE International Parallel and Distributed Processing Symposium (submitted), Anchorage, AK, May 2011.
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., 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)
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, 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., 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)
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, “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)
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)
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, 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)
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)
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., 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., “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., 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. 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., M. Faverge, T. Herault, M. Jacquelin, J. Langou, and Y. Robert, “Hierarchical QR Factorization Algorithms for Multi-core Cluster Systems,” Parallel Computing, vol. 39, issue 4-5, pp. 212-232, May 2013.  (1.43 MB)
Dongarra, J., H. Ltaeif, P. Luszczek, and V. M. Weaver, “Energy Footprint of Advanced Dense Numerical Linear Algebra using Tile Algorithms on Multicore Architecture,” The 2nd International Conference on Cloud and Green Computing (submitted), Xiangtan, Hunan, China, November 2012.  (329.5 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., “Network-Enabled Solvers: A Step Toward Grid-Based Computing,” SIAM News, vol. 34, no. 10, December 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., “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., 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.  (1.96 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, 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., “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., and J. Langou, “The Problem with the Linpack Benchmark Matrix Generator,” University of Tennessee Computer Science Technical Report, UT-CS-08-621 (also LAPACK Working Note 206), June 2008.  (136.41 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 P. Luszczek, “HPC Challenge: Design, History, and Implementation Highlights,” On the Road to Exascale Computing: Contemporary Architectures in High Performance Computing (to appear): Chapman & Hall/CRC Press, 00 2012.  (469.92 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., P. Beckman, P. Aerts, F. Cappello, T. Lippert, S. Matsuoka, P. Messina, T. Moore, R. Stevens, A. Trefethen, et al., “The International Exascale Software Project: A Call to Cooperative Action by the Global High Performance Community,” International Journal of High Performance Computing Applications (to appear), July 2009.  (203.04 KB)
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., 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., “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., Z. Chen, G. Bosilca, and J. Langou, “Disaster Survival Guide in Petascale Computing: An Algorithmic Approach,” in Petascale Computing: Algorithms and Applications (to appear): Chapman & Hall - CRC Press, 00 2007.  (260.18 KB)

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