Publications

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Danalis, A., H. Jagode, H. Hanumantharayappa, S. Ragate, and J. Dongarra, “Counter Inspection Toolkit: Making Sense out of Hardware Performance Events,” 11th International Workshop on Parallel Tools for High Performance Computing, Dresden, Germany, Cham, Switzerland: Springer, February 2019.  (216.39 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, 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, 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., 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, 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.
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.
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., 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, “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., 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, “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, 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)
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, “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, 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)
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., “Report on the TianHe-2A System,” Innovative Computing Laboratory Technical Report, no. ICL-UT-17-04: University of Tennessee, September 2017.  (7.15 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., 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)
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., M. Faverge, T. Herault, J. Langou, and Y. Robert, “Hierarchical QR Factorization Algorithms for Multi-Core Cluster Systems,” University of Tennessee Computer Science Technical Report (also Lawn 257), no. UT-CS-11-684, October 2011.  (405.71 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: O'Reilly Media, Inc., June 2007.  (257 KB)
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., 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., D. Laforenza, and S.. Orlando, “Recent Advances in Parallel Virtual Machine and Message Passing Interface,” Lecture Notes in Computer Science, vol. 2840: Springer-Verlag, Berlin, January 2003.
Dongarra, J., S. Hammarling, N. J. Higham, S. Relton, P. Valero-Lara, and M. Zounon, “The Design and Performance of Batched BLAS on Modern High-Performance Computing Systems,” International Conference on Computational Science (ICCS 2017), Zürich, Switzerland, Elsevier, June 2017.  (446.14 KB)
Dongarra, J., and V. Eijkhout, “Self Adapting Numerical Algorithm for Next Generation Applications,” International Journal of High Performance Computing Applications, vol. 17, no. 2, pp. 125-132, January 2003.  (479.18 KB)
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., and S. Tomov, An Introduction to the MAGMA project - Acceleration of Dense Linear Algebra : NVIDIA Webinar, June 2010.
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.
Dongarra, J., “Trends in High Performance Computing,” The Computer Journal, vol. 47, no. 4: The British Computer Society, pp. 399-403, 00 2004.  (455.96 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, January 2001.  (6.42 MB)
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., 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., “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., “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., 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., and S. Moore, “Empirical Performance Tuning of Dense Linear Algebra Software,” in Performance Tuning of Scientific Applications (to appear), 00 2010.
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., and V. Eijkhout, “Self-adapting Numerical Software for Next Generation Applications (LAPACK Working Note 157),” ICL Technical Report, no. ICL-UT-02-07, 00 2002.  (475.94 KB)

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