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2019
Danalis, A., H. Jagode, and J. Dongarra, PAPI's new Software-Defined Events for in-depth Performance Analysis , Dresden, Germany, 13th Parallel Tools Workshop, September 2019.  (3.14 MB)
Anzt, H., T. Ribizel, G. Flegar, E. Chow, and J. Dongarra, “ParILUT – A Parallel Threshold ILU for GPUs,” IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, IEEE, May 2019. DOI: 10.1109/IPDPS.2019.00033  (505.95 KB)
Cao, Q., Y. Pei, T. Herault, K. Akbudak, A. Mikhalev, G. Bosilca, H. Ltaief, D. Keyes, and J. Dongarra, “Performance Analysis of Tile Low-Rank Cholesky Factorization Using PaRSEC Instrumentation Tools,” Workshop on Programming and Performance Visualization Tools (ProTools 19) at SC19, Denver, CO, ACM, November 2019.  (429.55 KB)
Yamazaki, I., E. Chow, A. Bouteiller, and J. Dongarra, “Performance of Asynchronous Optimized Schwarz with One-sided Communication,” Parallel Computing, vol. 86, pp. 66-81, August 2019. DOI: 10.1016/j.parco.2019.05.004  (3.09 MB)
Dongarra, J., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, P. Wu, I. Yamazaki, A. YarKhan, M. Abalenkovs, N. Bagherpour, et al., “PLASMA: Parallel Linear Algebra Software for Multicore Using OpenMP,” ACM Transactions on Mathematical Software, vol. 45, issue 2, June 2019. DOI: 10.1145/3264491  (7.5 MB)
Abdelfattah, A., S. Tomov, and J. Dongarra, “Progressive Optimization of Batched LU Factorization on GPUs,” IEEE High Performance Extreme Computing Conference (HPEC’19), Waltham, MA, IEEE, September 2019.  (299.38 KB)
Dongarra, J., S. Gottlieb, and W. T. Kramer, “Race to Exascale,” Computing in Science and Engineering, vol. 21, issue 1, pp. 4-5, March 2019. DOI: 10.1109/MCSE.2018.2882574  (106.97 KB)
Gates, M., J. Kurzak, A. Charara, A. YarKhan, and J. Dongarra, SLATE: Design of a Modern Distributed and Accelerated Linear Algebra Library , Denver, CO, International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), November 2019.  (16.19 MB)
Gates, M., J. Kurzak, A. Charara, A. YarKhan, and J. Dongarra, “SLATE: Design of a Modern Distributed and Accelerated Linear Algebra Library,” International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Denver, CO, ACM, November 2019. DOI: 10.1145/3295500.3356223  (2.01 MB)
Charara, A., M. Gates, J. Kurzak, A. YarKhan, and J. Dongarra, “SLATE Developers' Guide,” SLATE Working Notes, no. 11, ICL-UT-19-02: Innovative Computing Laboratory, University of Tennessee, December 2019.  (1.68 MB)
Charara, A., J. Dongarra, M. Gates, J. Kurzak, and A. YarKhan, “SLATE Mixed Precision Performance Report,” Innovative Computing Laboratory Technical Report, no. ICL-UT-19-03: University of Tennessee, April 2019.  (1.04 MB)
Kurzak, J., M. Gates, A. Charara, A. YarKhan, and J. Dongarra, “SLATE Working Note 12: Implementing Matrix Inversions,” SLATE Working Notes, no. 12, ICL-UT-19-04: Innovative Computing Laboratory, University of Tennessee, June 2019.  (1.95 MB)
Gates, M., M. Al Farhan, A. Charara, J. Kurzak, D. Sukkari, A. YarKhan, and J. Dongarra, “SLATE Working Note 13: Implementing Singular Value and Symmetric/Hermitian Eigenvalue Solvers,” SLATE Working Notes, no. 13, ICL-UT-19-07: Innovative Computing Laboratory, University of Tennessee, September 2019.  (2.71 MB)
Danalis, A., H. Jagode, T. Herault, P. Luszczek, and J. Dongarra, “Software-Defined Events through PAPI,” 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Rio de Janeiro, Brazil, IEEE, May 2019. DOI: 10.1109/IPDPSW.2019.00069  (446.41 KB)
Zaitsev, D., S. Tomov, and J. Dongarra, “Solving Linear Diophantine Systems on Parallel Architectures,” IEEE Transactions on Parallel and Distributed Systems, vol. 30, issue 5, pp. 1158-1169, May 2019. DOI: http://dx.doi.org/10.1109/TPDS.2018.2873354  (802.97 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. DOI: 10.1145/3324989.3325719  (1.51 MB)
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)
Danalis, A., H. Jagode, D. Barry, and J. Dongarra, Understanding Native Event Semantics , Knoxville, TN, 9th JLESC Workshop, April 2019.  (2.33 MB)
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. DOI: 10.1016/j.parco.2017.12.006  (1.9 MB)
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)
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)
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. 7, 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)

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