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Danalis, A., H. Jagode, and J. Dongarra, Is your scheduling good? How would you know? , Bordeaux, France, 14th Scheduling for Large Scale Systems Workshop, June 2019.

(2.5 MB)

Bartlett, R., xSDK4ECP: Extreme-scale Scientific Software Development Kit for ECP (Poster) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.

(1.54 MB)

Hoefler, T., M. Copik, P. Beckman, A. Jones, I. Foster, M. Parashar, D. Reed, M. Troyer, T. Schulthess, D. Ernst, et al., XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing : arXiv, January 2024.

Dongarra, J., S. Tomov, P. Luszczek, J. Kurzak, M. Gates, I. Yamazaki, H. Anzt, A. Haidar, and A. Abdelfattah, “With Extreme Computing, the Rules Have Changed,” Computing in Science & Engineering, vol. 19, issue 3, pp. 52-62, May 2017.

(485.34 KB)

Barbut, Q., A. Benoit, T. Herault, Y. Robert, and F. Vivien, “When to checkpoint at the end of a fixed-length reservation?,” Fault Tolerance for HPC at eXtreme Scales (FTXS) Workshop, Denver, United States, August 2023.

Jagode, H., A. Danalis, and J. Dongarra, What it Takes to keep PAPI Instrumental for the HPC Community , Collegeville, MN, The 2019 Collegeville Workshop on Sustainable Scientific Software (CW3S19), July 2019.

(3.29 MB)

Jagode, H., A. Danalis, and J. Dongarra, “What it Takes to keep PAPI Instrumental for the HPC Community,” 1st Workshop on Sustainable Scientific Software (CW3S19), Collegeville, Minnesota, July 2019.

(50.57 KB)

Eijkhout, V., “The 'Weighted Modification' Incomplete Factorisation Method,” University of Tennessee Computer Science Department Technical Report, no. UT-CS-99-436, December 1999.

(198.71 KB)

Haidar, A., Y. Jia, P. Luszczek, S. Tomov, A. YarKhan, and J. Dongarra, “Weighted Dynamic Scheduling with Many Parallelism Grains for Offloading of Numerical Workloads to Multiple Varied Accelerators,” Proceedings of the 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA'15), vol. No. 5, Austin, TX, ACM, November 2015.

(347.6 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)

Anzt, H., S. Tomov, J. Dongarra, and V. Heuveline, “Weighted Block-Asynchronous Iteration on GPU-Accelerated Systems,” Tenth International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (Best Paper), Rhodes Island, Greece, August 2012.

(764.02 KB)

Fürlinger, K., and S. Moore, “Visualizing the Program Execution Control Flow of OpenMP Applications,” Proc. 4th International Workshop on OpenMP (IWOMP 2008), West Lafayette, Indiana, Lecture Notes in Computer Science 5004, pp. 181-190, January 2008.

(194.25 KB)

Haugen, B., S. Richmond, J. Kurzak, C. A. Steed, and J. Dongarra, “Visualizing Execution Traces with Task Dependencies,” 2nd Workshop on Visual Performance Analysis (VPA '15), Austin, TX, ACM, November 2015.

(927.5 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)

Kurzak, J., P. Luszczek, M. Gates, I. Yamazaki, and J. Dongarra, “Virtual Systolic Array for QR Decomposition,” 15th Workshop on Advances in Parallel and Distributed Computational Models, IEEE International Parallel & Distributed Processing Symposium (IPDPS 2013), Boston, MA, IEEE, May 2013.

(749.84 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)

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)

Ramakrishan, L., D. Nurmi, A. Mandal, C. Koelbel, D. Gannon, M. Huang, Y-S. Kee, G. Obertelli, K. Thyagaraja, R. Wolski, et al., “VGrADS: Enabling e-Science Workflows on Grids and Clouds with Fault Tolerance,” SC’09 The International Conference for High Performance Computing, Networking, Storage and Analysis (to appear), Portland, OR, 00 2009.

(648.82 KB)

Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Orti, “Variable-Size Batched LU for Small Matrices and Its Integration into Block-Jacobi Preconditioning,” 46th International Conference on Parallel Processing (ICPP), Bristol, United Kingdom, IEEE, August 2017.

Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Orti, “Variable-Size Batched Gauss-Jordan Elimination for Block-Jacobi Preconditioning on Graphics Processors,” Parallel Computing, vol. 81, pp. 131-146, January 2019.

(1.9 MB)

Anzt, H., J. Dongarra, G. Flegar, E. S. Quintana-Orti, and A. E. Thomas, “Variable-Size Batched Gauss-Huard for Block-Jacobi Preconditioning,” International Conference on Computational Science (ICCS 2017), vol. 108, Zurich, Switzerland, Procedia Computer Science, pp. 1783-1792, June 2017.

(512.57 KB)

Anzt, H., J. Dongarra, G. Flegar, and T. Gruetzmacher, “Variable-Size Batched Condition Number Calculation on GPUs,” SBAC-PAD, Lyon, France, September 2018.

(509.3 KB)

McCraw, H., A. Danalis, G. Bosilca, J. Dongarra, K. Kowalski, and T. Windus, “Utilizing Dataflow-based Execution for Coupled Cluster Methods,” 2014 IEEE International Conference on Cluster Computing, no. ICL-UT-14-02, Madrid, Spain, IEEE, September 2014.

(260.23 KB)

Eberius, D., T. Patinyasakdikul, and G. Bosilca, “Using Software-Based Performance Counters to Expose Low-Level Open MPI Performance Information,” EuroMPI, Chicago, IL, ACM, September 2017.

(745.58 KB)

Tsai, Y., P. Luszczek, and J. Dongarra, Using Quantized Integer in LU Factorization with Partial Pivoting (Poster) , Seattle, WA, SIAM Conference on Parallel Processing for Scientific Computing (SIAM PP20), February 2020.

(6.65 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)

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)

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)

Tomov, S., M. Faverge, P. Luszczek, and J. Dongarra, “Using MAGMA with PGI Fortran,” PGI Insider, November 2010.

(176.67 KB)

Zhong, D., Q. Cao, G. Bosilca, and J. Dongarra, “Using long vector extensions for MPI reductions,” Parallel Computing, vol. 109, pp. 102871, March 2022.

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.

(273.53 KB)

Fürlinger, K., J. Dongarra, and M. Gerndt, “On Using Incremental Profiling for the Performance Analysis of Shared Memory Parallel Applications,” Proceedings of the 13th International Euro-Par Conference on Parallel Processing (Euro-Par '07), Rennes, France, Springer LNCS, January 2007.

Haidar, A., S. Tomov, A. Abdelfattah, M. Zounon, and J. Dongarra, Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption , Frankfurt, Germany, ISC High Performance (ISC18), Best Poster Award, June 2018.

(3.01 MB)

Haidar, A., S. Tomov, A. Abdelfattah, M. Zounon, and J. Dongarra, “Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption,” ISC High Performance (ISC'18), Best Poster, Frankfurt, Germany, June 2018.

(3.01 MB)

Grützmacher, T., H. Anzt, and E. S. Quintana‐Ortí, “Using Ginkgo's memory accessor for improving the accuracy of memory‐bound low precision BLAS,” Software: Practice and Experience, vol. 532, issue 1, pp. 81 - 98, January Jan.

Baboulin, M., and S. Gratton, “Using dual techniques to derive componentwise and mixed condition numbers for a linear functional of a linear least squares solution,” University of Tennessee Computer Science Technical Report, UT-CS-08-622 (also LAPACK Working Note 207), January 2008.

(159.65 KB)

Zhong, D., P. Shamis, Q. Cao, G. Bosilca, and J. Dongarra, “Using Arm Scalable Vector Extension to Optimize Open MPI,” 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID 2020), Melbourne, Australia, IEEE/ACM, May 2020.

(359.95 KB)

Zhong, D., G. Bosilca, Q. Cao, and J. Dongarra, Using Advanced Vector Extensions AVX-512 for MPI Reduction (Poster) , Austin, TX, EuroMPI/USA '20: 27th European MPI Users' Group Meeting, September 2020.

(708.68 KB)

Zhong, D., Q. Cao, G. Bosilca, and J. Dongarra, “Using Advanced Vector Extensions AVX-512 for MPI Reduction,” EuroMPI/USA '20: 27th European MPI Users' Group Meeting, Austin, TX, September 2020.

(634.45 KB)

Lindquist, N., P. Luszczek, and J. Dongarra, “Using Additive Modifications in LU Factorization Instead of Pivoting,” 37th ACM International Conference on Supercomputing (ICS'23), Orlando, FL, ACM, June 2023.

(624.18 KB)

Agrawal, S., D. Arnold, S. Blackford, J. Dongarra, M. Miller, K. Sagi, Z. Shi, K. Seymour, and S. Vadhiyar, “Users' Guide to NetSolve v1.4.1,” ICL Technical Report, no. ICL-UT-02-05, June 2002.

(328.01 KB)

Moore, S., and J. Ralph, “User-Defined Events for Hardware Performance Monitoring,” Procedia Computer Science, vol. 4: Elsevier, pp. 2096-2104, May 2011.

(361.76 KB)

Bland, W., “User Level Failure Mitigation in MPI,” Euro-Par 2012: Parallel Processing Workshops, vol. 7640, Rhodes Island, Greece, Springer Berlin Heidelberg, pp. 499-504, August 2012.

(136.15 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)