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T
Tang, Y., “Technical Comparison between several representative checkpoint/rollback solutions for MPI programs,” ICL Technical Report, no. ICL-UT-06-09, January 2006.  (84.67 KB)
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)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Tensor Contractions using Optimized Batch GEMM Routines , San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.  (1.64 MB)
Tsai, Y-H. Mike, N. Beams, and H. Anzt, “Three-precision algebraic multigrid on GPUs,” Future Generation Computer Systems, July 2023.
Kennedy, K., J. Mellor-Crummey, K. Cooper, L. Torczon, F. Berman, A. Chien, D. Angulo, I. Foster, D. Gannon, L. Johnsson, et al., “Toward a Framework for Preparing and Executing Adaptive Grid Programs,” International Parallel and Distributed Processing Symposium: IPDPS 2002 Workshops, Fort Lauderdale, FL, pp. 0171, April 2002.  (64.5 KB)
Haidar, A., M. Gates, S. Tomov, and J. Dongarra, “Toward a scalable multi-GPU eigensolver via compute-intensive kernels and efficient communication,” Proceedings of the 27th ACM International Conference on Supercomputing (ICS '13), Eugene, Oregon, USA, ACM Press, June 2013.  (1.27 MB)
Baboulin, M., V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, T. Kolev, I. Masliah, and S. Tomov, Towards a High-Performance Tensor Algebra Package for Accelerators , Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC15), September 2015.  (1.76 MB)
Lopez, M. G., V. Larrea, W. Joubert, O. Hernandez, A. Haidar, S. Tomov, and J. Dongarra, “Towards Achieving Performance Portability Using Directives for Accelerators,” The International Conference for High Performance Computing, Networking, Storage and Analysis (SC'16), Third Workshop on Accelerator Programming Using Directives (WACCPD), Salt Lake City, Utah, Innovative Computing Laboratory, University of Tennessee, November 2016.  (567.02 KB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, “Towards Batched Linear Solvers on Accelerated Hardware Platforms,” 8th Workshop on General Purpose Processing Using GPUs (GPGPU 8) co-located with PPOPP 2015, San Francisco, CA, ACM, February 2015.  (403.74 KB)
Canning, A., J. Dongarra, J. Langou, O. Marques, S. Tomov, C. Voemel, and L-W. Wang, “Towards bulk based preconditioning for quantum dot computations,” IEEE/ACM Proceedings of HPCNano SC06 (to appear), January 2006.  (172.46 KB)
Anzt, H., Y. Chen Chen, T. Cojean, J. Dongarra, G. Flegar, P. Nayak, E. S. Quintana-Orti, Y. M. Tsai, and W. Wang, “Towards Continuous Benchmarking,” Platform for Advanced Scientific Computing Conference (PASC 2019), Zurich, Switzerland, ACM Press, June 2019.  (1.51 MB)
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)
Tomov, S., J. Dongarra, and M. Baboulin, “Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems,” University of Tennessee Computer Science Technical Report, UT-CS-08-632 (also LAPACK Working Note 210), January 2008.  (606.41 KB)
Abdelfattah, A., S. Tomov, and J. Dongarra, “Towards Half-Precision Computation for Complex Matrices: A Case Study for Mixed Precision Solvers on GPUs,” ScalA19: 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, IEEE, November 2019.  (523.87 KB) (3.42 MB)
Tseng, S-M., B. Nicolae, G. Bosilca, E. Jeannot, A. Chandramowlishwaran, and F. Cappello, “Towards Portable Online Prediction of Network Utilization Using MPI-Level Monitoring,” 2019 European Conference on Parallel Processing (Euro-Par 2019), Göttingen, Germany, Springer, August 2019.  (1.07 MB)
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., M. Gates, P. Luszczek, and S. Tomov, “Translational Process: Mathematical Software Perspective,” Journal of Computational Science, September 2020.  (752.59 KB)
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, “Translational Process: Mathematical Software Perspective,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-11, August 2020.  (752.59 KB)
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)
Yamazaki, I., T. Dong, S. Tomov, and J. Dongarra, “Tridiagonalization of a Symmetric Dense Matrix on a GPU Cluster,” The Third International Workshop on Accelerators and Hybrid Exascale Systems (AsHES), May 2013.
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)
Krzhizhanovskaya, V., G. Závodszky, M. Lees, J. Dongarra, P. Sloot, S. Brissos, and J. Teixeira, “Twenty Years of Computational Science,” International Conference on Computational Science (ICCS 2020), Amsterdam, Netherlands, June 2020.  (149.66 KB)
U
Haidar, A., C. Cao, J. Dongarra, P. Luszczek, and S. Tomov, “Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.51 MB)
Bosilca, G., A. Bouteiller, T. Herault, P. Lemariner, N. Ohm Saengpatsa, S. Tomov, and J. Dongarra, “A Unified HPC Environment for Hybrid Manycore/GPU Distributed Systems,” IEEE International Parallel and Distributed Processing Symposium (submitted), Anchorage, AK, May 2011.
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)
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)
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)
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)
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)
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)
V
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)
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)
W
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)
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)
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)
X
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.

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