Publications

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2022
Abdulah, S., Q. Cao, Y. Pei, G. Bosilca, J. Dongarra, M. G. Genton, D. E. Keyes, H. Ltaief, and Y. Sun, “Accelerating Geostatistical Modeling and Prediction With Mixed-Precision Computations: A High-Productivity Approach With PaRSEC,” IEEE Transactions on Parallel and Distributed Systems, vol. 33, issue 4, pp. 964 - 976, April 2022.
Abdelfattah, A., P. Ghysels, W. Boukaram, S. Tomov, X. Sherry Li, and J. Dongarra, “Addressing Irregular Patterns of Matrix Computations on GPUs and Their Impact on Applications Powered by Sparse Direct Solvers,” 2022 International Conference for High Performance Computing, Networking, Storage and Analysis (SC22), Dallas, TX, IEEE Computer Society, pp. 354-367, November 2022.  (1.57 MB)
Ayala, A., S. Tomov, P. Luszczek, S. Cayrols, G. Ragghianti, and J. Dongarra, “Analysis of the Communication and Computation Cost of FFT Libraries towards Exascale,” ICL Technical Report, no. ICL-UT-22-07: Innovative Computing Laboratory, July 2022.  (5.91 MB)
2021
Ayala, A., S. Tomov, A. Haidar, M.. Stoyanov, S. Cayrols, J. Li, G. Bosilca, and J. Dongarra, Accelerating FFT towards Exascale Computing : NVIDIA GPU Technology Conference (GTC2021), 2021.  (27.23 MB)
Ayala, A., S. Tomov, M. Stoyanov, A. Haidar, and J. Dongarra, “Accelerating Multi - Process Communication for Parallel 3-D FFT,” 2021 Workshop on Exascale MPI (ExaMPI), St. Louis, MO, USA, IEEE, December 2021.
Lindquist, N., P. Luszczek, and J. Dongarra, “Accelerating Restarted GMRES with Mixed Precision Arithmetic,” IEEE Transactions on Parallel and Distributed Systems, June 2021.  (572.4 KB)
2020
Hendrickson, B., P. Messina, B. Bland, J. Chen, P. Colella, E. Dart, J. Dongarra, T. Dunning, I. Foster, R. Gerber, et al., ASCR@40: Four Decades of Department of Energy Leadership in Advanced Scientific Computing Research : Advanced Scientific Computing Advisory Committee (ASCAC), US Department of Energy, August 2020.
Hendrickson, B., P. Messina, B. Bland, J. Chen, P. Colella, E. Dart, J. Dongarra, T. Dunning, I. Foster, R. Gerber, et al., ASCR@40: Highlights and Impacts of ASCR’s Programs : US Department of Energy’s Office of Advanced Scientific Computing Research, June 2020.
Lopez, F., E. Chow, S. Tomov, and J. Dongarra, “Asynchronous SGD for DNN Training on Shared-Memory Parallel Architectures,” Workshop on Scalable Deep Learning over Parallel And Distributed Infrastructures (ScaDL 2020), May 2020.  (188.51 KB)
Lopez, F., E. Chow, S. Tomov, and J. Dongarra, “Asynchronous SGD for DNN Training on Shared-Memory Parallel Architectures,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-04: University of Tennessee, Knoxville, March 2020.  (188.51 KB)
2019
Anzt, H., J. Dongarra, G. Flegar, N. J. Higham, and E. S. Quintana-Orti, “Adaptive Precision in Block-Jacobi Preconditioning for Iterative Sparse Linear System Solvers,” Concurrency and Computation: Practice and Experience, vol. 31, no. 6, pp. e4460, March 2019.  (341.54 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,” Parallel Computing, vol. 81, pp. 1–21, January 2019.  (3.27 MB)
2018
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.  (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.  (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.  (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.  (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.  (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.  (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.  (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.  (720.15 KB)
2017
Jagode, H., A. Danalis, and J. Dongarra, “Accelerating NWChem Coupled Cluster through Dataflow-Based Execution,” The International Journal of High Performance Computing Applications, pp. 1–13, January 2017.  (4.07 MB)
Abdelfattah, A., M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, T. Kolev, I. Masliah, et al., Accelerating Tensor Contractions in High-Order FEM with MAGMA Batched , Atlanta, GA, SIAM Conference on Computer Science and Engineering (SIAM CSE17), Presentation, March 2017.  (9.29 MB)
Gates, M., J. Kurzak, P. Luszczek, Y. Pei, and J. Dongarra, “Autotuning Batch Cholesky Factorization in CUDA with Interleaved Layout of Matrices,” Parallel and Distributed Processing Symposium Workshops (IPDPSW), Orlando, FL, IEEE, June 2017.
2016
Haidar, A., A. Abdelfattah, V. Dobrev, I. Karlin, T. Kolev, S. Tomov, and J. Dongarra, Accelerating Tensor Contractions for High-Order FEM on CPUs, GPUs, and KNLs , Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC16), Poster, September 2016.  (4.29 MB)
Anzt, H., M. Baboulin, J. Dongarra, Y. Fournier, F. Hulsemann, A. Khabou, and Y. Wang, “Accelerating the Conjugate Gradient Algorithm with GPU in CFD Simulations,” VECPAR, 2016.
Herrmann, J., G. Bosilca, T. Herault, L. Marchal, Y. Robert, and J. Dongarra, “Assessing the Cost of Redistribution followed by a Computational Kernel: Complexity and Performance Results,” Parallel Computing, vol. 52, pp. 22-41, February 2016.  (2.06 MB)
2015
Gates, M., H. Anzt, J. Kurzak, and J. Dongarra, “Accelerating Collaborative Filtering for Implicit Feedback Datasets using GPUs,” 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, IEEE, November 2015.  (1.02 MB)
Jagode, H., A. Danalis, G. Bosilca, and J. Dongarra, “Accelerating NWChem Coupled Cluster through dataflow-based Execution,” 11th International Conference on Parallel Processing and Applied Mathematics (PPAM 2015), Krakow, Poland, Springer International Publishing, September 2015.  (452.82 KB)
Anzt, H., S. Tomov, and J. Dongarra, “Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product,” Spring Simulation Multi-Conference 2015 (SpringSim'15), Alexandria, VA, SCS, April 2015.  (1.46 MB)
Anzt, H., W. Sawyer, S. Tomov, P. Luszczek, and J. Dongarra, “Acceleration of GPU-based Krylov solvers via Data Transfer Reduction,” International Journal of High Performance Computing Applications, 2015.
Anzt, H., J. Dongarra, and E. S. Quintana-Orti, “Adaptive Precision Solvers for Sparse Linear Systems,” 3rd International Workshop on Energy Efficient Supercomputing (E2SC '15), Austin, TX, ACM, November 2015.
Bouteiller, A., T. Herault, G. Bosilca, P. Du, and J. Dongarra, “Algorithm-based Fault Tolerance for Dense Matrix Factorizations, Multiple Failures, and Accuracy,” ACM Transactions on Parallel Computing, vol. 1, issue 2, no. 10, pp. 10:1-10:28, January 2015.  (1.14 MB)
Chow, E., H. Anzt, and J. Dongarra, “Asynchronous Iterative Algorithm for Computing Incomplete Factorizations on GPUs,” International Supercomputing Conference (ISC 2015), Frankfurt, Germany, July 2015.
2014
Gates, M., A. Haidar, and J. Dongarra, “Accelerating Eigenvector Computation in the Nonsymmetric Eigenvalue Problem,” VECPAR 2014, Eugene, OR, June 2014.  (199.44 KB)
Dongarra, J., M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, and I. Yamazaki, “Accelerating Numerical Dense Linear Algebra Calculations with GPUs,” Numerical Computations with GPUs: Springer International Publishing, pp. 3-28, 2014.  (1.06 MB)
Anzt, H., S. Tomov, and J. Dongarra, “Accelerating the LOBPCG method on GPUs using a blocked Sparse Matrix Vector Product,” University of Tennessee Computer Science Technical Report, no. UT-EECS-14-731: University of Tennessee, October 2014.  (1.83 MB)
Yamazaki, I., T. Mary, J. Kurzak, S. Tomov, and J. Dongarra, “Access-averse Framework for Computing Low-rank Matrix Approximations,” First International Workshop on High Performance Big Graph Data Management, Analysis, and Mining, Washington, DC, October 2014.
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, “Achieving numerical accuracy and high performance using recursive tile LU factorization with partial pivoting,” Concurrency and Computation: Practice and Experience, vol. 26, issue 7, pp. 1408-1431, May 2014.  (1.96 MB)
Bosilca, G., A. Bouteiller, T. Herault, Y. Robert, and J. Dongarra, “Assessing the Impact of ABFT and Checkpoint Composite Strategies,” 16th Workshop on Advances in Parallel and Distributed Computational Models, IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.02 MB)
2013
Baboulin, M., J. Dongarra, J. Herrmann, and S. Tomov, “Accelerating Linear System Solutions Using Randomization Techniques,” ACM Transactions on Mathematical Software (also LAWN 246), vol. 39, issue 2, February 2013.  (358.79 KB)
Bosilca, G., A. Bouteiller, T. Herault, Y. Robert, and J. Dongarra, “Assessing the impact of ABFT and Checkpoint composite strategies,” University of Tennessee Computer Science Technical Report, no. ICL-UT-13-03, 2013.  (968.47 KB)
2012
Dong, T., T. Kolev, R. Rieben, V. Dobrev, S. Tomov, and J. Dongarra, “Acceleration of the BLAST Hydro Code on GPU,” Supercomputing '12 (poster), Salt Lake City, Utah, SC12, November 2012.
Du, P., A. Bouteiller, G. Bosilca, T. Herault, and J. Dongarra, “Algorithm-Based Fault Tolerance for Dense Matrix Factorization,” Proceedings of the 17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP 2012, New Orleans, LA, USA, ACM, pp. 225-234, February 2012.  (865.79 KB)
Donfack, S., J. Dongarra, M. Faverge, M. Gates, J. Kurzak, P. Luszczek, and I. Yamazaki, “On Algorithmic Variants of Parallel Gaussian Elimination: Comparison of Implementations in Terms of Performance and Numerical Properties,” University of Tennessee Computer Science Technical Report, no. UT-CS-13-715, July 2013, 2012.  (358.98 KB)
Luszczek, P., and J. Dongarra, “Anatomy of a Globally Recursive Embedded LINPACK Benchmark,” 2012 IEEE High Performance Extreme Computing Conference, Waltham, MA, pp. 1-6, September 2012.  (204.74 KB)
Kurzak, J., S. Tomov, and J. Dongarra, “Autotuning GEMM Kernels for the Fermi GPU,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 11, November 2012.  (742.5 KB)
2011
Baboulin, M., J. Dongarra, J. Herrmann, and S. Tomov, “Accelerating Linear System Solutions Using Randomization Techniques,” INRIA RR-7616 / LAWN #246 (presented at International AMMCS’11), Waterloo, Ontario, Canada, July 2011.  (358.79 KB)
Dongarra, J., M. Faverge, H. Ltaeif, and P. Luszczek, “Achieving Numerical Accuracy and High Performance using Recursive Tile LU Factorization,” University of Tennessee Computer Science Technical Report (also as a LAWN), no. ICL-UT-11-08, September 2011.  (618.53 KB)

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