Publications

Export 971 results:
Filters: Author is Jack Dongarra  [Clear All Filters]
2017
Abdelfattah, A., H. Anzt, A. Bouteiller, A. Danalis, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, et al., Roadmap for the Development of a Linear Algebra Library for Exascale Computing: SLATE: Software for Linear Algebra Targeting Exascale,” SLATE Working Notes, no. 01, ICL-UT-17-02: Innovative Computing Laboratory, University of Tennessee, June 2017.  (2.8 MB)
Yamazaki, I., S. Tomov, and J. Dongarra, Sampling Algorithms to Update Truncated SVD,” IEEE International Conference on Big Data, Boston, MA, IEEE, December 2017.  (700.79 KB)
Luszczek, P., J. Kurzak, I. Yamazaki, D. Keffer, and J. Dongarra, Scaling Point Set Registration in 3D Across Thread Counts on Multicore and Hardware Accelerator Platforms through Autotuning for Large Scale Analysis of Scientific Point Clouds,” IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2017), Boston, MA, IEEE, December 2017. DOI: 10.1109/BigData.2017.8258258  (6.71 MB)
Abdelfattah, A., M. Baboulin, V. Dobrev, J. Dongarra, A. Haidar, I. Karlin, T. Kolev, I. Masliah, and S. Tomov, Small Tensor Operations on Advanced Architectures for High-Order Applications,” University of Tennessee Computer Science Technical Report, no. UT-EECS-17-749: Innovative Computing Laboratory, University of Tennessee, April 2017.  (1.09 MB)
Baboulin, M., J. Dongarra, A. Remy, S. Tomov, and I. Yamazaki, Solving Dense Symmetric Indefinite Systems using GPUs,” Concurrency and Computation: Practice and Experience, vol. 29, issue 9, March 2017. DOI: 10.1002/cpe.4055  (1.94 MB)
Yamazaki, I., S. Nooshabadi, S. Tomov, and J. Dongarra, Structure-aware Linear Solver for Realtime Convex Optimization for Embedded Systems,” IEEE Embedded Systems Letters, vol. 9, issue 3, pp. 61–64, May 2017. DOI: 10.1109/LES.2017.2700401  (339.11 KB)
Luszczek, P., J. Kurzak, I. Yamazaki, and J. Dongarra, Towards Numerical Benchmark for Half-Precision Floating Point Arithmetic,” 2017 IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, IEEE, September 2017. DOI: 10.1109/HPEC.2017.8091031  (1.67 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. DOI: 10.1016/j.procs.2017.05.186  (512.57 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. DOI: 10.1109/ICPP.2017.18
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. DOI: 10.1109/MCSE.2017.48  (485.34 KB)
2018
Dongarra, J., V. Getov, and K. Walsh, The 30th Anniversary of the Supercomputing Conference: Bringing the Future Closer—Supercomputing History and the Immortality of Now,” Computer, vol. 51, issue 10, pp. 74–85, November 2018. DOI: 10.1109/MC.2018.3971352  (1.73 MB)
Jagode, H., A. Danalis, and J. Dongarra, Accelerating NWChem Coupled Cluster through dataflow-based Execution,” The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 540--551, July 2018. DOI: 10.1177/1094342016672543  (1.68 MB)
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. DOI: 10.1016/j.jocs.2018.01.007  (2.18 MB)
Gates, M., S. Tomov, and J. Dongarra, Accelerating the SVD Two Stage Bidiagonal Reduction and Divide and Conquer Using GPUs,” Parallel Computing, vol. 74, pp. 3–18, May 2018. DOI: 10.1016/j.parco.2017.10.004  (1.34 MB)
Luo, X., W. Wu, G. Bosilca, T. Patinyasakdikul, L. Wang, and J. Dongarra, ADAPT: An Event-Based Adaptive Collective Communication Framework,” The 27th International Symposium on High-Performance Parallel and Distributed Computing (HPDC '18), Tempe, Arizona, ACM Press, June 2018. DOI: 10.1145/3208040.3208054  (493.65 KB)
Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, M. Baboulin, J. Falcou, and J. Dongarra, Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-09: Innovative Computing Laboratory, University of Tennessee, September 2018.  (3.74 MB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Analysis and Design Techniques towards High-Performance and Energy-Efficient Dense Linear Solvers on GPUs,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 12, pp. 2700–2712, December 2018. DOI: 10.1109/TPDS.2018.2842785  (2.53 MB)
Yamazaki, I., A. Abdelfattah, A. Ida, S. Ohshima, S. Tomov, R. Yokota, and J. Dongarra, Analyzing Performance of BiCGStab with Hierarchical Matrix on GPU Clusters,” IEEE International Parallel and Distributed Processing Symposium (IPDPS), Vancouver, BC, Canada, IEEE, May 2018.  (1.37 MB)
Balaprakash, P., J. Dongarra, T. Gamblin, M. Hall, J. Hollingsworth, B. Norris, and R. Vuduc, Autotuning in High-Performance Computing Applications,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2068–2083, November 2018. DOI: 10.1109/JPROC.2018.2841200  (2.5 MB)
Dongarra, J., M. Gates, J. Kurzak, P. Luszczek, and Y. Tsai, Autotuning Numerical Dense Linear Algebra for Batched Computation With GPU Hardware Accelerators,” Proceedings of the IEEE, vol. 106, issue 11, pp. 2040–2055, November 2018. DOI: 10.1109/JPROC.2018.2868961  (2.53 MB)
Luszczek, P., J. Kurzak, I. Yamazaki, D. Keffer, V. Maroulas, and J. Dongarra, Autotuning Techniques for Performance-Portable Point Set Registration in 3D,” Supercomputing Frontiers and Innovations, vol. 5, no. 4, December 2018. DOI: 10.14529/jsfi180404  (720.15 KB)
Dongarra, J., I. Duff, M. Gates, A. Haidar, S. Hammarling, N. J. Higham, J. Hogg, P. Valero Lara, P. Luszczek, M. Zounon, et al., Batched BLAS (Basic Linear Algebra Subprograms) 2018 Specification , July 2018.  (483.05 KB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures,” Journal of Computational Science, vol. 26, pp. 226–236, May 2018. DOI: 10.1016/j.jocs.2018.01.005  (3.73 MB)
Asch, M., T. Moore, R. M. Badia, M. Beck, P. Beckman, T. Bidot, F. Bodin, F. Cappello, A. Choudhary, B. R. de Supinski, et al., Big Data and Extreme-Scale Computing: Pathways to Convergence - Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry,” The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 435–479, July 2018. DOI: 10.1177/1094342018778123  (1.29 MB)
Sun, J., J. Fu, J. Drake, Q. Zhu, A. Haidar, M. Gates, S. Tomov, and J. Dongarra, Computational Benefit of GPU Optimization for Atmospheric Chemistry Modeling,” Journal of Advances in Modeling Earth Systems, vol. 10, issue 8, pp. 1952–1969, August 2018. DOI: 10.1029/2018MS001276  (3.4 MB)
Bouteiller, A., G. Bosilca, T. Herault, and J. Dongarra, Data Movement Interfaces to Support Dataflow Runtimes,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-03: University of Tennessee, May 2018.  (210.94 KB)
Haidar, A., A. Abdelfattah, M. Zounon, P. Wu, S. Pranesh, S. Tomov, and J. Dongarra, The Design of Fast and Energy-Efficient Linear Solvers: On the Potential of Half-Precision Arithmetic and Iterative Refinement Techniques,” International Conference on Computational Science (ICCS 2018), vol. 10860, Wuxi, China, Springer, pp. 586–600, June 2018. DOI: 10.1007/978-3-319-93698-7_45  (487.88 KB)
Bosilca, G., A. Bouteiller, T. Herault, V. Le Fèvre, Y. Robert, and J. Dongarra, Distributed Termination Detection for HPC Task-Based Environments,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-14: University of Tennessee, June 2018.
Le Fèvre, V., G. Bosilca, A. Bouteiller, T. Herault, A. Hori, Y. Robert, and J. Dongarra, Do moldable applications perform better on failure-prone HPC platforms?,” 11th Workshop on Resiliency in High Performance Computing in Clusters, Clouds, and Grids, Turin, Italy, Springer Verlag, August 2018.  (360.72 KB)
Tomov, S., A. Haidar, D. Schultz, and J. Dongarra, Evaluation and Design of FFT for Distributed Accelerated Systems,” ECP WBS 2.3.3.09 Milestone Report, no. FFT-ECP ST-MS-10-1216: Innovative Computing Laboratory, University of Tennessee, October 2018.  (7.53 MB)
Jagode, H., A. Danalis, R. Hoque, M. Faverge, and J. Dongarra, Evaluation of Dataflow Programming Models for Electronic Structure Theory,” Concurrency and Computation: Practice and Experience: Special Issue on Parallel and Distributed Algorithms, vol. 2018, issue e4490, pp. 1–20, May 2018. DOI: 10.1002/cpe.4490  (1.69 MB)
Bosilca, G., A. Bouteiller, A. Guermouche, T. Herault, Y. Robert, P. Sens, and J. Dongarra, A Failure Detector for HPC Platforms,” The International Journal of High Performance Computing Applications, vol. 32, issue 1, pp. 139–158, January 2018. DOI: 10.1177/1094342017711505  (1.04 MB)
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. DOI: 10.1109/TPDS.2017.2783929  (832.92 KB)
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. DOI: 10.1109/SC.2018.00050  (642.51 KB)
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., M. Gates, J. Kurzak, P. Luszczek, and J. Dongarra, Implementation of the C++ API for Batch BLAS,” SLATE Working Notes, no. 07, ICL-UT-18-04: Innovative Computing Laboratory, University of Tennessee, June 2018.  (1.07 MB)
Anzt, H., T. Huckle, J. Bräckle, and J. Dongarra, Incomplete Sparse Approximate Inverses for Parallel Preconditioning,” Parallel Computing, vol. 71, pp. 1–22, January 2018. DOI: 10.1016/j.parco.2017.10.003  (1.24 MB)
Ghysels, P., S. Li, A. YarKhan, and J. Dongarra, Initial Integration and Evaluation of SLATE and STRUMPACK,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-11: University of Tennessee, December 2018.  (249.78 KB)
YarKhan, A., G. Ragghianti, J. Dongarra, M. Cawkwell, D. Perez, and A. Voter, Initial Integration and Evaluation of SLATE Parallel BLAS in LATTE,” Innovative Computing Laboratory Technical Report, no. ICL-UT-18-07: Innovative Computing Laboratory, University of Tennessee, June 2018.  (366.6 KB)
Haidar, A., H. Jagode, P. Vaccaro, A. YarKhan, S. Tomov, and J. Dongarra, Investigating Power Capping toward Energy-Efficient Scientific Applications,” Concurrency Computation: Practice and Experience, vol. 2018, issue e4485, pp. 1-14, April 2018. DOI: 10.1002/cpe.4485  (1.2 MB)
Anzt, H., and J. Dongarra, A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs,” SBAC-PAD, Lyon, France, IEEE, 2018.  (237.68 KB)
Gates, M., A. Charara, J. Kurzak, A. YarKhan, I. Yamazaki, and J. Dongarra, Least Squares Performance Report,” SLATE Working Notes, no. 09, ICL-UT-18-10: Innovative Computing Laboratory, University of Tennessee, December 2018.  (1.76 MB)
Kurzak, J., M. Gates, I. Yamazaki, A. Charara, A. YarKhan, J. Finney, G. Ragghianti, P. Luszczek, and J. Dongarra, Linear Systems Performance Report,” SLATE Working Notes, no. 08, ICL-UT-18-08: Innovative Computing Laboratory, University of Tennessee, September 2018.  (1.64 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)
Herault, T., Y. Robert, A. Bouteiller, D. Arnold, K. Ferreira, G. Bosilca, and J. Dongarra, Optimal Cooperative Checkpointing for Shared High-Performance Computing Platforms,” 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Best Paper Award, Vancouver, BC, Canada, IEEE, May 2018. DOI: 10.1109/IPDPSW.2018.00127  (899.3 KB)
Anzt, H., M. Kreutzer, E. Ponce, G. D. Peterson, G. Wellein, and J. Dongarra, Optimization and Performance Evaluation of the IDR Iterative Krylov Solver on GPUs,” The International Journal of High Performance Computing Applications, vol. 32, no. 2, pp. 220–230, March 2018. DOI: 10.1177/1094342016646844  (2.08 MB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, Optimizing GPU Kernels for Irregular Batch Workloads: A Case Study for Cholesky Factorization,” IEEE High Performance Extreme Computing Conference (HPEC’18), Waltham, MA, IEEE, September 2018.  (729.87 KB)
Danalis, A., H. Jagode, and J. Dongarra, PAPI: Counting outside the Box , Barcelona, Spain, 8th JLESC Meeting, April 2018.
Jagode, H., A. Danalis, and J. Dongarra, PAPI's New Software-Defined Events for In-Depth Performance Analysis , Lyon, France, CCDSC 2018: Workshop on Clusters, Clouds, and Data for Scientific Computing, September 2018.

Pages