Publications

Export 1049 results:
Journal Article
Yamazaki, I., J. Kurzak, P. Wu, M. Zounon, and J. Dongarra, Symmetric Indefinite Linear Solver using OpenMP Task on Multicore Architectures,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 8, pp. 1879–1892, August 2018. DOI: 10.1109/TPDS.2018.2808964  (2.88 MB)
Dorris, J., A. YarKhan, J. Kurzak, P. Luszczek, and J. Dongarra, Task Based Cholesky Decomposition on Xeon Phi Architectures using OpenMP,” International Journal of Computational Science and Engineering (IJCSE), vol. 17, no. 3, October 2018. DOI: http://dx.doi.org/10.1504/IJCSE.2018.095851
Kennedy, K., B. Broom, K. Cooper, J. Dongarra, R. Fowler, D. Gannon, L. Johnsson, J. Mellor-Crummey, and L. Torczon, Telescoping Languages: A Strategy for Automatic Generation of Scientific Problem-Solving Systems from Annotated Libraries,” Journal of Parallel and Distributed Computing, vol. 61, no. 12, pp. 1803-1826, December 2001.  (386.37 KB)
Sourbier, F., A. Haidar, L. Giraud, H. Ben-Hadj-Ali, S. Operto, and J. Virieux, Three-dimensional parallel frequency-domain visco-acoustic wave modelling based on a hybrid direct/iterative solver.,” To appear in Geophysical Prospecting journal., 00 2011.  (1.04 MB)
Calland, P-Y., J. Dongarra, and Y. Robert, Tiling on Systems with Communication/Computation Overlap,” Concurrency: Practice and Experience, vol. 11, no. 3, pp. 139-153, January 1999.  (286.14 KB)
Strohmaier, E., H. Meuer, J. Dongarra, and H. D. Simon, The TOP500 List and Progress in High-Performance Computing,” IEEE Computer, vol. 48, issue 11, pp. 42-49, November 2015. DOI: doi:10.1109/MC.2015.338
Anzt, H., G. Flegar, T. Gruetzmacher, and E. S. Quintana-Ortí, Toward a Modular Precision Ecosystem for High-Performance Computing,” The International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1069-1078, November 2019. DOI: 10.1177/1094342019846547  (1.93 MB)
Haidar, A., H. Ltaeif, and J. Dongarra, Toward High Performance Divide and Conquer Eigensolver for Dense Symmetric Matrices,” SIAM Journal on Scientific Computing (Accepted), July 2012.
Haidar, A., H. Ltaeif, and J. Dongarra, Toward High Performance Divide and Conquer Eigensolver for Dense Symmetric Matrices.,” Submitted to SIAM Journal on Scientific Computing (SISC), 00 2011.
Agullo, E., L. Giraud, A. Guermouche, A. Haidar, and J. Roman, Towards a Complexity Analysis of Sparse Hybrid Linear Solvers,” PARA 2010, Reykjavik, Iceland, June 2010.
Anzt, H., T. Cojean, and E. Kuhn, Towards a New Peer Review Concept for Scientific Computing ensuring Technical Quality, Software Sustainability, and Result Reproducibility,” Proceedings in Applied Mathematics and Mechanics, vol. 19, issue 1, November 2019. DOI: 10.1002/pamm.201900490
Vadhiyar, S., G. Fagg, and J. Dongarra, Towards an Accurate Model for Collective Communications,” International Journal of High Performance Applications, Special Issue: Automatic Performance Tuning, vol. 18, no. 1, pp. 159-167, January 2004.  (250.73 KB)
Tomov, S., J. Dongarra, and M. Baboulin, Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems,” Parallel Computing, vol. 36, no. 5-6, pp. 232-240, 00 2010.  (606.41 KB)
Hoefler, T., Y-S. Dai, and J. Dongarra, Towards Efficient MapReduce Using MPI,” Lecture Notes in Computer Science, Recent Advances in Parallel Virtual Machine and Message Passing Interface - 16th European PVM/MPI Users' Group Meeting, vol. 5759, Espoo, Finland, Springer Berlin / Heidelberg, pp. 240-249, 00 2009.
Benoit, A., A. Cavelan, V. Le Fèvre, Y. Robert, and H. Sun, Towards Optimal Multi-Level Checkpointing,” IEEE Transactions on Computers, vol. 66, issue 7, pp. 1212–1226, July 2017. DOI: 10.1109/TC.2016.2643660  (1.39 MB)
Jagode, H., A. Knuepfer, J. Dongarra, M. Jurenz, M. S. Mueller, and W. E. Nagel, Trace-based Performance Analysis for the Petascale Simulation Code FLASH,” International Journal of High Performance Computing Applications (to appear), 00 2010.  (887.54 KB)
Seymour, K., A. YarKhan, and J. Dongarra, Transparent Cross-Platform Access to Software Services using GridSolve and GridRPC,” in Cloud Computing and Software Services: Theory and Techniques (to appear): CRC Press, 00 2009.
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., A Tribute to Gene Golub,” Computing in Science and Engineering: IEEE, pp. 5, January 2008.
Yamazaki, I., T. Dong, R. Solcà, S. Tomov, J. Dongarra, and T. C. Schulthess, Tridiagonalization of a dense symmetric matrix on multiple GPUs and its application to symmetric eigenvalue problems,” Concurrency and Computation: Practice and Experience, October 2013.  (1.71 MB)
Hiroyasu, T., M. Miki, H. Shimosaka, M. Sano, Y. Tanimura, Y. Mimura, S. Yoshimura, and J. Dongarra, Truss Structural Optimization Using NetSolve System,” Meeting of the Japan Society of Mechanical Engineers, Kyoto University, Kyoto, Japan, October 2002.  (450.65 KB)
Du, P., M. Parsons, E. Fuentes, S-L. Shaw, and J. Dongarra, Tuning Principal Component Analysis for GRASS GIS on Multi-core and GPU Architectures,” FOSS4G 2010, Barcelona, Spain, September 2010.  (1.57 MB)
Bosilca, G., A. Bouteiller, E. Brunet, F. Cappello, J. Dongarra, A. Guermouche, T. Herault, Y. Robert, F. Vivien, and D. Zaidouni, Unified Model for Assessing Checkpointing Protocols at Extreme-Scale,” Concurrency and Computation: Practice and Experience, November 2013. DOI: 10.1002/cpe.3173  (894.61 KB)
Aliaga, J. I., H. Anzt, M. Castillo, J. C. Fernández, G. León, J. Pérez, and E. S. Quintana-Ortí, Unveiling the Performance-energy Trade-off in Iterative Linear System Solvers for Multithreaded Processors,” Concurrency and Computation: Practice and Experience, vol. 27, issue 4, pp. 885-904, September 2014. DOI: 10.1002/cpe.3341  (1.83 MB)
Blackford, S., J. Demmel, J. Dongarra, I. Duff, S. Hammarling, G. Henry, M. Heroux, L. Kaufman, A. Lumsdaine, A. Petitet, et al., An Updated Set of Basic Linear Algebra Subprograms (BLAS),” ACM Transactions on Mathematical Software, vol. 28, no. 2, pp. 135-151, December 2002. DOI: 10.1145/567806.567807  (228.33 KB)
Anzt, H., E. Chow, J. Saak, and J. Dongarra, Updating Incomplete Factorization Preconditioners for Model Order Reduction,” Numerical Algorithms, vol. 73, issue 3, no. 3, pp. 611–630, February 2016. DOI: 10.1007/s11075-016-0110-2  (565.34 KB)
Voemel, C., S. Tomov, L-W. Wang, O. Marques, and J. Dongarra, The Use of Bulk States to Accelerate the Band Edge State Calculation of a Semiconductor Quantum Dot,” Journal of Computational Physics, vol. 223, pp. 774-782, 00 2007.  (452.6 KB)
Voemel, C., S. Tomov, L-W. Wang, O. Marques, and J. Dongarra, The use of bulk states to accelerate the band edge state calculation of a semiconductor quantum dot,” Journal of Computational Physics (submitted), January 2006.  (337.08 KB)
Moore, S., and J. Ralph, User-Defined Events for Hardware Performance Monitoring,” Procedia Computer Science, vol. 4: Elsevier, pp. 2096-2104, May 2011. DOI: 10.1016/j.procs.2011.04.229  (361.76 KB)
Chow, E., H. Anzt, J. Scott, and J. Dongarra, Using Jacobi Iterations and Blocking for Solving Sparse Triangular Systems in Incomplete Factorization Preconditioning,” Journal of Parallel and Distributed Computing, vol. 119, pp. 219–230, November 2018. DOI: 10.1016/j.jpdc.2018.04.017  (273.53 KB)
Tomov, S., M. Faverge, P. Luszczek, and J. Dongarra, Using MAGMA with PGI Fortran,” PGI Insider, November 2010.  (176.67 KB)
Buttari, A., J. Dongarra, J. Kurzak, P. Luszczek, and S. Tomov, Using Mixed Precision for Sparse Matrix Computations to Enhance the Performance while Achieving 64-bit Accuracy,” ACM Transactions on Mathematical Software, vol. 34, no. 4, pp. 17-22, 00 2008.  (364.48 KB)
Giraud, L., A. Haidar, and S. Pralet, Using multiple levels of parallelism to enhance the performance of domain decomposition solvers,” Parallel Computing, vol. 36, no. 5-6: Elsevier journals, pp. 285-296, 00 2010.  (418.57 KB)
Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, Variable-Size Batched Gauss–Jordan Elimination for Block-Jacobi Preconditioning on Graphics Processors,” Parallel Computing, January 2018. DOI: 10.1016/j.parco.2017.12.006  (1.9 MB)
Casanova, H., T. Bartol, F. Berman, A. Birnbaum, J. Dongarra, M. Ellisman, M. Faerman, E. Gockay, M. Miller, G. Obertelli, et al., The Virtual Instrument: Support for Grid-enabled Scientific Simulations,” International Journal of High Performance Computing Applications, vol. 18, no. 1, pp. 3-17, January 2004.  (282.16 KB)
Casanova, H., T. Bartol, F. Berman, A. Birnbaum, J. Dongarra, M. Ellisman, M. Faerman, E. Gockay, M. Miller, G. Obertelli, et al., The Virtual Instrument: Support for Grid-enabled Scientific Simulations,” Journal of Parallel and Distributed Computing (submitted), October 2002.  (282.16 KB)
Lee, DW., and J. Dongarra, VisPerf: Monitoring Tool for Grid Computing,” Lecture Notes in Computer Science, vol. 2659: Springer Verlag, Heidelberg, pp. 233-243, 00 2003.  (835.09 KB)
Anzt, H., J. Dongarra, and V. Heuveline, Weighted Block-Asynchronous Relaxation for GPU-Accelerated Systems,” SIAM Journal on Computing (submitted), March 2012.  (811.01 KB)
Miscellaneous
Reed, D., and J. Dongarra, Exascale Computing and Big Data,” Communications of the ACM, vol. 58, no. 7: ACM, pp. 56-68, July 2015. DOI: 10.1145/2699414  (7.3 MB)
Dongarra, J., The HPL Benchmark: Past, Present & Future , ISC High Performance, Frankfurt, Germany, July 2016.  (3.41 MB)
Poster
Cheng, X., A. Soma, E. D'Azevedo, K. Wong, and S. Tomov, Accelerating 2D FFT: Exploit GPU Tensor Cores through Mixed-Precision , Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), ACM Student Research Poster, November 2018.  (740.37 KB)
Haidar, A., A. Abdelfattah, V. Dobrev, I. Karlin, T. Kolev, S. Tomov, and J. Dongarra, Accelerating Tensor Contractions for High-Order FEM on CPUs, GPUs, and KNLs , Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC16), Poster, September 2016.  (4.29 MB)
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.
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Cholesky Factorization on Batches of Matrices with Fixed and Variable Sizes , San Jose, CA, GPU Technology Conference (GTC16), Poster, April 2016.  (480.51 KB)
Baboulin, M., J. Demmel, J. Dongarra, S. Tomov, and V. Volkov, Enhancing the Performance of Dense Linear Algebra Solvers on GPUs (in the MAGMA Project) , Austin, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC08), November 2008.  (5.28 MB)
Tomov, S., A. Haidar, A. Ayala, D. Schultz, and J. Dongarra, FFT-ECP Fast Fourier Transform , Houston, TX, 2019 ECP Annual Meeting (Research Poster), January 2019.  (1.51 MB)
Shaiek, H., S. Tomov, A. Ayala, A. Haidar, and J. Dongarra, GPUDirect MPI Communications and Optimizations to Accelerate FFTs on Exascale Systems,” EuroMPI'19 Posters, Zurich, Switzerland, no. icl-ut-19-06: ICL, September 2019.  (2.25 MB)
Haidar, A., A. Abdelfattah, S. Tomov, and J. Dongarra, Harnessing GPU's Tensor Cores Fast FP16 Arithmetic to Speedup Mixed-Precision Iterative Refinement Solvers and Achieve 74 Gflops/Watt on Nvidia V100 , San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.  (2.96 MB)
Abdelfattah, A., J. Dongarra, A. Haidar, S. Tomov, and I. Yamazaki, MATEDOR: MAtrix, TEnsor, and Deep-learning Optimized Routines , Dallas, TX, The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Research Poster, November 2018.  (2.55 MB)
Haidar, A., S. Tomov, A. Abdelfattah, I. Yamazaki, and J. Dongarra, MAtrix, TEnsor, and Deep-learning Optimized Routines (MATEDOR) , Washington, DC, NSF PI Meeting, Poster, April 2018. DOI: 10.6084/m9.figshare.6174143.v3  (2.4 MB)

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