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2024
Melnichenko, M., O. Balabanov, R. Murray, J. Demmel, M. W. Mahoney, and P. Luszczek, CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT) : arXiv, February 2024.
Anzt, H., A. Huebl, and X. S. Li, “Then and Now: Improving Software Portability, Productivity, and 100× Performance,” Computing in Science & Engineering, pp. 1 - 10, April 2024.
2023
Thiyagalingam, J., G. von Laszewski, J. Yin, M. Emani, J. Papay, G. Barrett, P. Luszczek, A. Tsaris, C. Kirkpatrick, F. Wang, et al., “AI Benchmarking for Science: Efforts from the MLCommons Science Working Group,” Lecture Notes in Computer Science, vol. 13387: Springer International Publishing, pp. 47 - 64, January 2023.
Thiyagalingam, J., G. von Laszewski, J. Yin, M. Emani, J. Papay, G. Barrett, P. Luszczek, A. Tsaris, C. Kirkpatrick, F. Wang, et al., “AI Benchmarking for Science: Efforts from the MLCommons Science Working Group,” Lecture Notes in Computer Science, vol. 13387: Springer International Publishing, pp. 47 - 64, January 2023.
Luszczek, P., W. M. Sid-Lakhdar, and J. Dongarra, “Combining multitask and transfer learning with deep Gaussian processes for autotuning-based performance engineering,” The International Journal of High Performance Computing Applications, March 2023.
Hoefler, T., B. Stevens, A. F. Prein, J. Baehr, T. Schulthess, T. F. Stocker, J. Taylor, D. Klocke, P. Manninen, P. M. Forster, et al., Earth Virtualization Engines - A Technical Perspective , September 2023.
Li, J., G. Bosilca, A. Bouteiller, and B. Nicolae, “Elastic deep learning through resilient collective operations,” SC-W 2023: Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Denver, CO, ACM, November 2023.
Lindquist, N., P. Luszczek, and J. Dongarra, Generalizing Random Butterfly Transforms to Arbitrary Matrix Sizes : arXiv, December 2023.
Lindquist, N., P. Luszczek, and J. Dongarra, Generalizing Random Butterfly Transforms to Arbitrary Matrix Sizes : arXiv, December 2023.
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.
Sid-Lakhdar, W., S. Cayrols, D. Bielich, A. Abdelfattah, P. Luszczek, M. Gates, S. Tomov, H. Johansen, D. Williams-Young, T. Davis, et al., “PAQR: Pivoting Avoiding QR factorization,” 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS), St. Petersburg, FL, USA, IEEE, 2023.
Aggarwal, I., P. Nayak, A. Kashi, and H. Anzt, “Preconditioners for Batched Iterative Linear Solvers on GPUs,” Smoky Mountains Computational Sciences and Engineering Conference, vol. 169075: Springer Nature Switzerland, pp. 38 - 53, January 2023.
Cao, Q., S. Abdulah, H. Ltaief, M. G. Genton, D. Keyes, and G. Bosilca, “Reducing Data Motion and Energy Consumption of Geospatial Modeling Applications Using Automated Precision Conversion,” 2023 IEEE International Conference on Cluster Computing (CLUSTER), Santa Fe, NM, USA, IEEE, November 2023.
Lindquist, N., P. Luszczek, and J. Dongarra, “Using Additive Modifications in LU Factorization Instead of Pivoting,” 37th ACM International Conference on Supercomputing (ICS'23), Orlando, FL, ACM, June 2023.  (624.18 KB)
Lindquist, N., P. Luszczek, and J. Dongarra, “Using Additive Modifications in LU Factorization Instead of Pivoting,” 37th ACM International Conference on Supercomputing (ICS'23), Orlando, FL, ACM, June 2023.  (624.18 KB)
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)
Kashi, A., P. Nayak, D. Kulkarni, A. Scheinberg, P. Lin, and H. Anzt, “Batched sparse iterative solvers on GPU for the collision operator for fusion plasma simulations,” 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), Lyon, France, IEEE, July 2022.  (1.26 MB)
Bosilca, G., A. Bouteiller, T. Herault, V. Le Fèvre, Y. Robert, and J. Dongarra, “Comparing Distributed Termination Detection Algorithms for Modern HPC Platforms,” International Journal of Networking and Computing, vol. 12, issue 1, pp. 26 - 46, January 2022.
Sid-Lakhdar, W. M., M. Aznaveh, P. Luszczek, and J. Dongarra, “Deep Gaussian process with multitask and transfer learning for performance optimization,” 2022 IEEE High Performance Extreme Computing Conference (HPEC), pp. 1-7, September 2022.
Cao, Q., G. Bosilca, N. Losada, W. Wu, D. Zhong, and J. Dongarra, “Evaluating Data Redistribution in PaRSEC,” IEEE Transactions on Parallel and Distributed Systems, vol. 33, no. 8, pp. 1856-1872, August 2022.  (3.19 MB)
Ayala, A., S. Tomov, P. Luszczek, S. Cayrols, G. Ragghianti, and J. Dongarra, “FFT Benchmark Performance Experiments on Systems Targeting Exascale,” ICL Technical Report, no. ICL-UT-22-02, March 2022.  (5.87 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)
Cayrols, S., J. Li, G. Bosilca, S. Tomov, A. Ayala, and J. Dongarra, “Lossy all-to-all exchange for accelerating parallel 3-D FFTs on hybrid architectures with GPUs,” 2022 IEEE International Conference on Cluster Computing (CLUSTER), pp. 152-160, September 2022.
Cayrols, S., J. Li, G. Bosilca, S. Tomov, A. Ayala, and J. Dongarra, “Mixed precision and approximate 3D FFTs: Speed for accuracy trade-off with GPU-aware MPI and run-time data compression,” ICL Technical Report, no. ICL-UT-22-04, May 2022.  (706.14 KB)
Bak, S., C. Bertoni, S. Boehm, R. Budiardja, B. M. Chapman, J. Doerfert, M. Eisenbach, H. Finkel, O. Hernandez, J. Huber, et al., “OpenMP application experiences: Porting to accelerated nodes,” Parallel Computing, vol. 109, March 2022.
Bak, S., C. Bertoni, S. Boehm, R. Budiardja, B. M. Chapman, J. Doerfert, M. Eisenbach, H. Finkel, O. Hernandez, J. Huber, et al., “OpenMP application experiences: Porting to accelerated nodes,” Parallel Computing, vol. 109, March 2022.
Bak, S., C. Bertoni, S. Boehm, R. Budiardja, B. M. Chapman, J. Doerfert, M. Eisenbach, H. Finkel, O. Hernandez, J. Huber, et al., “OpenMP application experiences: Porting to accelerated nodes,” Parallel Computing, vol. 109, March 2022.
Sid-Lakhdar, W. M., S. Cayrols, D. Bielich, A. Abdelfattah, P. Luszczek, M. Gates, S. Tomov, H. Johansen, D. Williams-Young, T. A. Davis, et al., “PAQR: Pivoting Avoiding QR factorization,” ICL Technical Report, no. ICL-UT-22-06, June 2022.  (364.85 KB)
Funk, Y., M. Götz, and H. Anzt, “Prediction of Optimal Solvers for Sparse Linear Systems Using Deep Learning,” 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP), Philadelphia, PA, Society for Industrial and Applied Mathematics, pp. 14 - 24.
Murray, R., J. Demmel, M. W. Mahoney, B. N. Erichson, M. Melnichenko, O. Asif Malik, L. Grigori, P. Luszczek, M. Dereziński, M. E. Lopes, et al., “Randomized Numerical Linear Algebra: A Perspective on the Field with an Eye to Software,” University of California, Berkeley EECS Technical Report, no. UCB/EECS-2022-258: University of California, Berkeley, November 2022.  (1.05 MB) (1.54 MB)
Murray, R., J. Demmel, M. W. Mahoney, B. N. Erichson, M. Melnichenko, O. Asif Malik, L. Grigori, P. Luszczek, M. Dereziński, M. E. Lopes, et al., “Randomized Numerical Linear Algebra: A Perspective on the Field with an Eye to Software,” University of California, Berkeley EECS Technical Report, no. UCB/EECS-2022-258: University of California, Berkeley, November 2022.  (1.05 MB) (1.54 MB)
Murray, R., J. Demmel, M. W. Mahoney, B. N. Erichson, M. Melnichenko, O. Asif Malik, L. Grigori, P. Luszczek, M. Dereziński, M. E. Lopes, et al., “Randomized Numerical Linear Algebra: A Perspective on the Field with an Eye to Software,” University of California, Berkeley EECS Technical Report, no. UCB/EECS-2022-258: University of California, Berkeley, November 2022.  (1.05 MB) (1.54 MB)
Murray, R., J. Demmel, M. W. Mahoney, B. N. Erichson, M. Melnichenko, O. Asif Malik, L. Grigori, P. Luszczek, M. Dereziński, M. E. Lopes, et al., “Randomized Numerical Linear Algebra: A Perspective on the Field with an Eye to Software,” University of California, Berkeley EECS Technical Report, no. UCB/EECS-2022-258: University of California, Berkeley, November 2022.  (1.05 MB) (1.54 MB)
Cao, Q., S. Abdulah, R. Alomairy, Y. Pei, P. Nag, G. Bosilca, J. Dongarra, M. G. Genton, D. Keyes, H. Ltaief, et al., “Reshaping Geostatistical Modeling and Prediction for Extreme-Scale Environmental Applications,” 2022 International Conference for High Performance Computing, Networking, Storage and Analysis (SC22), Dallas, TX, IEEE Press, November 2022.
Agullo, E., M. Altenbernd, H. Anzt, L. Bautista-Gomez, T. Benacchio, L. Bonaventura, H-J. Bungartz, S. Chatterjee, F. M. Ciorba, N. DeBardeleben, et al., “Resiliency in numerical algorithm design for extreme scale simulations,” The International Journal of High Performance Computing Applications, vol. 36371337212766180823, issue 2, pp. 251 - 285, March 2022.
Agullo, E., M. Altenbernd, H. Anzt, L. Bautista-Gomez, T. Benacchio, L. Bonaventura, H-J. Bungartz, S. Chatterjee, F. M. Ciorba, N. DeBardeleben, et al., “Resiliency in numerical algorithm design for extreme scale simulations,” The International Journal of High Performance Computing Applications, vol. 36371337212766180823, issue 2, pp. 251 - 285, March 2022.
Luszczek, P., and C. Brown, “Surrogate ML/AI Model Benchmarking for FAIR Principles' Conformance,” 2022 IEEE High Performance Extreme Computing Conference (HPEC): IEEE, September 2022.
Lindquist, N., M. Gates, P. Luszczek, and J. Dongarra, “Threshold Pivoting for Dense LU Factorization,” ScalAH22: 13th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems , Dallas, Texas, IEEE, November 2022.  (721.77 KB)
Lindquist, N., M. Gates, P. Luszczek, and J. Dongarra, “Threshold Pivoting for Dense LU Factorization,” ScalAH22: 13th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems , Dallas, Texas, IEEE, November 2022.  (721.77 KB)
2021
Kovalchuk, S. V., V. V. Krzhizhanovskaya, PMA. Sloot, G. Závodszky, M. H. Lees, M. Paszyński, and J. Dongarra, “20 years of computational science: Selected papers from 2020 International Conference on Computational Science,” Journal of Computational Science, vol. 53, pp. 101395–101395, 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)
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)
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)
Herault, T., Y. Robert, G. Bosilca, R. Harrison, C. Lewis, E. Valeev, and J. Dongarra, “Distributed-Memory Multi-GPU Block-Sparse Tensor Contraction for Electronic Structure,” 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021), Portland, OR, IEEE, May 2021.
Ayala, A., S. Tomov, P. Luszczek, S. Cayrols, G. Ragghianti, and J. Dongarra, “Interim Report on Benchmarking FFT Libraries on High Performance Systems,” Innovative Computing Laboratory Technical Report, no. ICL-UT-21-03: University of Tennessee, July 2021.  (2.68 MB)
Penchoff, D. A., E. Valeev, H. Jagode, P. Luszczek, A. Danalis, G. Bosilca, R. J. Harrison, J. Dongarra, and T. L. Windus, “An Introduction to High Performance Computing and Its Intersection with Advances in Modeling Rare Earth Elements and Actinides,” Rare Earth Elements and Actinides: Progress in Computational Science Applications, vol. 1388, Washington, DC, American Chemical Society, pp. 3-53, October 2021.
Jagode, H., H. Anzt, H. Ltaief, and P. Luszczek, Lecture Notes in Computer Science: High Performance Computing , vol. 12761: Springer International Publishing, 2021.
Jagode, H., H. Anzt, H. Ltaief, and P. Luszczek, Lecture Notes in Computer Science: High Performance Computing , vol. 12761: Springer International Publishing, 2021.

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