Publications

Export 1274 results:
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
D
Danalis, A., H. Jagode, and J. Dongarra, PAPI's new Software-Defined Events for in-depth Performance Analysis , Dresden, Germany, 13th Parallel Tools Workshop, September 2019.  (3.14 MB)
Danalis, A., H. Jagode, D. Barry, and J. Dongarra, Understanding Native Event Semantics , Knoxville, TN, 9th JLESC Workshop, April 2019.  (2.33 MB)
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, 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., 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)
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., 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, “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., 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, “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., 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., 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.
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., M. A. Heroux, and P. Luszczek, “High-Performance Conjugate-Gradient Benchmark: A New Metric for Ranking High-Performance Computing Systems,” The International Journal of High Performance Computing Applications, 2015.  (336.19 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., 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., and A. Lastovetsky, “An Overview of Heterogeneous High Performance and Grid Computing,” Engineering the Grid (to appear): Nova Science Publishers, Inc., 00 2004.  (199.93 KB)
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., 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., “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., 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., 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., “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., 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., “A Not So Simple Matter of Software,” NCSA Access Online: NCSA, 00 2005.  (457.69 KB)
Dongarra, J., A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and A. YarKhan, “Model-Driven One-Sided Factorizations on Multicore, Accelerated Systems,” Supercomputing Frontiers and Innovations, vol. 1, issue 1, 2014.  (1.86 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., 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., The HPL Benchmark: Past, Present & Future , ISC High Performance, Frankfurt, Germany, July 2016.  (3.41 MB)
Dongarra, J., H. Meuer, H. D. Simon, and E. Strohmaier, “High Performance Computing Trends,” HERMIS, vol. 2, pp. 155-163, November 2001.
Dongarra, J., “The evolution of mathematical software,” Communications of the ACM, vol. 65227, issue 12, pp. 66 - 72, December 2022.
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., “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., 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 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)

Pages