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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)
Haidar, A., S. Tomov, J. Dongarra, and N. J. Higham, Harnessing GPU Tensor Cores for Fast FP16 Arithmetic to Speed up Mixed-Precision Iterative Refinement Solvers,” The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Dallas, TX, IEEE, November 2018.  (642.51 KB)
Fagg, G., and J. Dongarra, HARNESS Fault Tolerant MPI Design, Usage and Performance Issues,” Future Generation Computer Systems, vol. 18, no. 8, pp. 1127-1142, January 2002.  (403.41 KB)
Fagg, G., A. Bukovsky, and J. Dongarra, HARNESS and Fault Tolerant MPI,” Parallel Computing, vol. 27, no. 11, pp. 1479-1496, January 2001.  (164.2 KB)
Beck, M., J. Dongarra, G. Fagg, A. Geist, P. Gray, J. Kohl, M. Migliardi, K. Moore, T. Moore, P. Papadopoulous, et al., HARNESS: A Next Generation Distributed Virtual Machine,” International Journal on Future Generation Computer Systems, vol. 15, no. 5-6, pp. 571-582, January 1999.  (183.78 KB)
Wolf, F., and B. Mohr, Hardware-Counter Based Automatic Performance Analysis of Parallel Programs,” Advances in Parallel Computing, vol. 13, Dresden, Germany, Elsevier, pp. 753-760, January 2004, 2003.
Agrawal, S., Hardware Software Server in NetSolve,” ICL Technical Report, no. ICL-UT-02-02, January 2002.  (221.4 KB)
Wong, K., S. Tomov, and J. Dongarra, Hands-on Research and Training in High-Performance Data Sciences, Data Analytics, and Machine Learning for Emerging Environments,” ISC High Performance, Frankfurt, Germany, Springer International Publishing, June 2019.  (1016.52 KB)
Luo, X., W. Wu, G. Bosilca, Y. Pei, Q. Cao, T. Patinyasakdikul, D. Zhong, and J. Dongarra, HAN: A Hierarchical AutotuNed Collective Communication Framework,” IEEE Cluster Conference, Kobe, Japan, Best Paper Award, IEEE Computer Society Press, September 2020.  (764.05 KB)
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Haidar, A., A. Abdelfattah, M. Zounon, S. Tomov, and J. Dongarra, A Guide for Achieving High Performance with Very Small Matrices on GPUs: A Case Study of Batched LU and Cholesky Factorizations,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 5, pp. 973–984, May 2018.  (832.92 KB)
YarKhan, A., J. Dongarra, and K. Seymour, GridSolve: The Evolution of Network Enabled Solver,” Grid-Based Problem Solving Environments: IFIP TC2/WG 2.5 Working Conference on Grid-Based Problem Solving Environments (Prescott, AZ, July 2006): Springer, pp. 215-226, 00 2007.  (377.48 KB)
Seymour, K., H. Nakada, S. Matsuoka, J. Dongarra, C. Lee, and H. Casanova, GridRPC: A Remote Procedure Call API for Grid Computing,” ICL Technical Report, no. ICL-UT-02-06, November 2002.  (287.73 KB)
Miller, M., C. Moulding, J. Dongarra, and C. Johnson, Grid-Enabling Problem Solving Environments: A Case Study of SCIRUN and NetSolve,” Proceedings of the High Performance Computing Symposium (HPC 2001) in 2001 Advanced Simulation Technologies Conference, Seattle, Washington, Society for Modeling and Simulation International, April 2001.  (144.19 KB)
Cunha, M., J. Telles, A. YarKhan, and J. Dongarra, Grid Computing applied to the Boundary Element Method,” Proceedings of the First International Conference on Parallel, Distributed and Grid Computing for Engineering, vol. 27, no. :104203/9027, Stirlingshire, UK, Civil-Comp Press, 00 2009.
Vadhiyar, S., J. Dongarra, and A. YarKhan, GrADSolve - RPC for High Performance Computing on the Grid,” Lecture Notes in Computer Science, Proceedings of the 9th International Euro-Par Conference, vol. 2790, Klagenfurt, Austria, Springer-Verlag, Berlin, pp. 394-403, January 2003.  (125.96 KB)
Vadhiyar, S., and J. Dongarra, GrADSolve - A Grid-based RPC System for Remote Invocation of Parallel Software,” Journal of Parallel and Distributed Computing (submitted), March 2003.  (241.3 KB)
Berman, F., A. Chien, K. Cooper, J. Dongarra, I. Foster, D. Gannon, L. Johnsson, K. Kennedy, C. Kesselman, J. Mellor-Crummey, et al., The GrADS Project: Software Support for High-Level Grid Application Development,” International Journal of High Performance Applications and Supercomputing, vol. 15, no. 4, pp. 327-344, January 2001.  (271.52 KB)
Berman, F., A. Chien, K. Cooper, J. Dongarra, I. Foster, D. Gannon, L. Johnsson, K. Kennedy, C. Kesselman, D. Reed, et al., The GrADS Project: Software Support for High-Level Grid Application Development,” Technical Report, February 2000.  (347.41 KB)
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)
Abdelfattah, A., S. Tomov, P. Luszczek, H. Anzt, and J. Dongarra, GPU-based LU Factorization and Solve on Batches of Matrices with Band Structure,” SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, CO, ACM, November 2023.
Wu, W., G. Bosilca, R. vandeVaart, S. Jeaugey, and J. Dongarra, GPU-Aware Non-contiguous Data Movement In Open MPI,” 25th International Symposium on High-Performance Parallel and Distributed Computing (HPDC'16), Kyoto, Japan, ACM, June 2016.  (482.32 KB)
Anzt, H., E. Ponce, G. D. Peterson, and J. Dongarra, GPU-accelerated Co-design of Induced Dimension Reduction: Algorithmic Fusion and Kernel Overlap,” 2nd International Workshop on Hardware-Software Co-Design for High Performance Computing, Austin, TX, ACM, November 2015.  (1.46 MB)
Anzt, H., P. Luszczek, J. Dongarra, and V. Heuveline, GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement,” EuroPar 2012 (also LAWN 260), Rhodes Island, Greece, August 2012.  (662.98 KB)
Anzt, H., P. Luszczek, J. Dongarra, and V. Heuveline, GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement,” University of Tennessee Computer Science Technical Report UT-CS-11-690 (also Lawn 260), December 2011.  (662.98 KB)
Abdelfattah, A., V. Barra, N. Beams, R. Bleile, J. Brown, J-S. Camier, R. Carson, N. Chalmers, V. Dobrev, Y. Dudouit, et al., GPU algorithms for Efficient Exascale Discretizations,” Parallel Computing, vol. 108, pp. 102841, 2021.
Patinyasakdikul, T., D. Eberius, G. Bosilca, and N. Hjelm, Give MPI Threading a Fair Chance: A Study of Multithreaded MPI Designs,” IEEE Cluster, Albuquerque, NM, IEEE, September 2019.  (220.84 KB)
Cojean, T., Y-H. Mike Tsai, and H. Anzt, Ginkgo—A math library designed for platform portability,” Parallel Computing, vol. 111, pp. 102902, February 2022.
Anzt, H., T. Cojean, Y-C. Chen, F. Goebel, T. Gruetzmacher, P. Nayak, T. Ribizel, Y-H. Tsai, and J. Dongarra, Ginkgo: A Node-Level Sparse Linear Algebra Library for HPC (Poster) , Houston, TX, 2020 Exascale Computing Project Annual Meeting, February 2020.  (699 KB)
Anzt, H., T. Cojean, G. Flegar, F. Göbel, T. Grützmacher, P. Nayak, T. Ribizel, Y. Mike Tsai, and E. S. Quintana-Ortí, Ginkgo: A Modern Linear Operator Algebra Framework for High Performance Computing,” ACM Transactions on Mathematical Software, vol. 48, issue 12, pp. 1 - 33, March 2022.  (4.2 MB)
Cojean, T., P. Nayak, T. Ribizel, N. Beams, Y-H. Mike Tsai, M. Koch, F. Göbel, T. Grützmacher, and H. Anzt, Ginkgo - A math library designed to accelerate Exascale Computing Project science applications,” The International Journal of High Performance Computing Applications, August 2024.
Anzt, H., T. Cojean, Y-C. Chen, F. Goebel, T. Gruetzmacher, P. Nayak, T. Ribizel, and Y-H. Tsai, Ginkgo: A High Performance Numerical Linear Algebra Library,” Journal of Open Source Software, vol. 5, issue 52, August 2020.  (721.84 KB)
Anzt, H., N. Beams, T. Cojean, F. Göbel, T. Grützmacher, A. Kashi, P. Nayak, T. Ribizel, and Y. M. Tsai, Gingko: A Sparse Linear Algebrea Library for HPC : 2021 ECP Annual Meeting, April 2021.  (893.04 KB)
Herault, T., Y. Robert, G. Bosilca, and J. Dongarra, Generic Matrix Multiplication for Multi-GPU Accelerated Distributed-Memory Platforms over PaRSEC,” ScalA'19: 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, IEEE, November 2019.  (260.69 KB)
Han, L., V. Le Fèvre, L-C. Canon, Y. Robert, and F. Vivien, A Generic Approach to Scheduling and Checkpointing Workflows,” International Journal of High Performance Computing Applications, vol. 33, issue 6, pp. 1255-1274, November 2019.  (555.01 KB)
Han, L., V. Le Fèvre, L-C. Canon, Y. Robert, and F. Vivien, A Generic Approach to Scheduling and Checkpointing Workflows,” The 47th International Conference on Parallel Processing (ICPP 2018), Eugene, OR, IEEE Computer Society Press, August 2018.  (737.11 KB)
Han, L., V. Le Fèvre, L-C. Canon, Y. Robert, and F. Vivien, A Generic Approach to Scheduling and Checkpointing Workflows,” Int. Journal of High Performance Computing Applications, vol. 33, no. 6, pp. 1255-1274, 2019.  (555.01 KB)
Lindquist, N., P. Luszczek, and J. Dongarra, Generalizing Random Butterfly Transforms to Arbitrary Matrix Sizes : arXiv, December 2023.
Schuchart, J., P. Nookala, M. Mahdi Javanmard, T. Herault, E. F. Valeev, G. Bosilca, and R. J. Harrison, Generalized Flow-Graph Programming Using Template Task-Graphs: Initial Implementation and Assessment,” 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), Lyon, France, IEEE, July 2022.
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, The Future of Supercomputing: An Interim Report,” National Research Council, Washington, D.C., The National Academies Press, January 2003.
Tomov, S., and J. Dongarra, The Future of Computing: Software Libraries , Savannah, GA, DOD CREATE Developers' Review, Keynote Presentation, February 2012.  (6.76 MB)
Kurzak, J., and J. Dongarra, Fully Dynamic Scheduler for Numerical Computing on Multicore Processors,” University of Tennessee Computer Science Department Technical Report, UT-CS-09-643 (Also LAPACK Working Note 220), 00 2009.  (488.24 KB)
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)
Fagg, G., and J. Dongarra, FT-MPI: Fault Tolerant MPI, Supporting Dynamic Applications in a Dynamic World,” Lecture Notes in Computer Science: Proceedings of EuroPVM-MPI 2000, (Hungary: Springer Verlag, 2000), pp. V1908,346-353, January 2000.  (51.95 KB)
Bosilca, G., A. Bouteiller, A. Danalis, T. Herault, and J. Dongarra, From Serial Loops to Parallel Execution on Distributed Systems,” International European Conference on Parallel and Distributed Computing (Euro-Par '12), Rhodes, Greece, August 2012.  (203.08 KB)
Tang, C., A. Bouteiller, T. Herault, M G. Venkata, and G. Bosilca, From MPI to OpenSHMEM: Porting LAMMPS,” OpenSHMEM and Related Technologies. Experiences, Implementations, and Technologies, Annapolis, MD, USA, Springer International Publishing, pp. 121–137, 2015.
Du, P., R. Weber, P. Luszczek, S. Tomov, G. D. Peterson, and J. Dongarra, From CUDA to OpenCL: Towards a Performance-portable Solution for Multi-platform GPU Programming,” Parallel Computing, vol. 38, no. 8, pp. 391-407, August 2012.  (1.64 MB)
Cao, Q., R. Alomairy, Y. Pei, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, A Framework to Exploit Data Sparsity in Tile Low-Rank Cholesky Factorization,” IEEE International Parallel and Distributed Processing Symposium (IPDPS), July 2022.  (1.03 MB)
Kabir, K., A. Haidar, S. Tomov, A. Bouteiller, and J. Dongarra, A Framework for Out of Memory SVD Algorithms,” ISC High Performance 2017, pp. 158–178, June 2017.  (393.22 KB)
Haidar, A., T. Dong, S. Tomov, P. Luszczek, and J. Dongarra, Framework for Batched and GPU-resident Factorization Algorithms to Block Householder Transformations,” ISC High Performance, Frankfurt, Germany, Springer, July 2015.  (778.26 KB)
Jagode, H., A. Danalis, and J. Dongarra, Formulation of Requirements for New PAPI++ Software Package: Part I: Survey Results,” PAPI++ Working Notes, no. 1, ICL-UT-20-02: Innovative Computing Laboratory, University of Tennessee Knoxville, January 2020.  (1.49 MB)

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