Publications

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Danalis, A., P. Luszczek, G. Marin, J. Vetter, and J. Dongarra, “BlackjackBench: Portable Hardware Characterization with Automated Results Analysis,” The Computer Journal, March 2013.  (408.45 KB)
Danalis, A., H. Jagode, and J. Dongarra, Software-Defined Events through PAPI for In-Depth Analysis of Application Performance , Basel, Switzerland, 5th Platform for Advanced Scientific Computing Conference (PASC18), July 2018.
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, 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)
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)
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,” 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)
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)
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, “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)
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., 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 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., and et al., “Remembering Ken Kennedy,” SciDAC Review, vol. 5, no. 2007, 00 2007.  (519.68 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., 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., 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. Gates, P. Luszczek, and S. Tomov, “Translational process: Mathematical software perspective,” Journal of Computational Science, vol. 52, pp. 101216, 2021.
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., “The evolution of mathematical software,” Communications of the ACM, vol. 65227, issue 12, pp. 66 - 72, December 2022.
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., 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., “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., 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., and S. Moore, “Empirical Performance Tuning of Dense Linear Algebra Software,” in Performance Tuning of Scientific Applications (to appear), 00 2010.
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., 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., 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., 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., “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.  (1.06 MB)
Dongarra, J., S. Hammarling, N. J. Higham, S. Relton, and M. Zounon, “Optimized Batched Linear Algebra for Modern Architectures,” Euro-Par 2017, Santiago de Compostela, Spain, Springer, August 2017.  (618.33 KB)
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., 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., “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)

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