Publications

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Lu, Y., I. Yamazaki, F. Ino, Y. Matsushita, S. Tomov, and J. Dongarra, Reducing the Amount of out-of-core Data Access for GPU-Accelerated Randomized SVD,” Concurrency and Computation: Practice and Experience, April 2020. DOI: 10.1002/cpe.5754 (1.43 MB)
Reed, D., D. Gannon, and J. Dongarra, Reinventing High Performance Computing: Challenges and Opportunities,” ICL Technical Report, no. ICL-UT-22-03, March 2022.  (1.36 MB)
Lindquist, N., P. Luszczek, and J. Dongarra, Replacing Pivoting in Distributed Gaussian Elimination with Randomized Techniques,” 2020 IEEE/ACM 11th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), Atlanta, GA, IEEE, November 2020.  (184.6 KB)
Dongarra, J., Report on the Fujitsu Fugaku System,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-06: University of Tennessee, June 2020.  (3.3 MB)
Dongarra, J., and A. Geist, Report on the Oak Ridge National Laboratory's Frontier System,” ICL Technical Report, no. ICL-UT-22-05, May 2022.  (16.87 MB)
Moore, S., D. Cronk, K. London, and J. Dongarra, Review of Performance Analysis Tools for MPI Parallel Programs,” European Parallel Virtual Machine / Message Passing Interface Users’ Group Meeting, Lecture Notes in Computer Science 2131, Greece, Springer Verlag, Berlin, pp. 241-248, September 2001. DOI: 10.1007/3-540-45417-9_34 (39.61 KB)
Bosilca, G., A. Bouteiller, T. Herault, V. Le Fèvre, Y. Robert, and J. Dongarra, Revisiting Credit Distribution Algorithms for Distributed Termination Detection,” 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW): IEEE, pp. 611–620, 2021. DOI: 10.1109/IPDPSW52791.2021.00095
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)
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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)
Ayala, A., S. Tomov, M. Stoyanov, and J. Dongarra, Scalability Issues in FFT Computation,” International Conference on Parallel Computing Technologies: Springer, pp. 279–287, 2021. DOI: 10.1007/978-3-030-86359-3_21
Luszczek, P., Y. Tsai, N. Lindquist, H. Anzt, and J. Dongarra, Scalable Data Generation for Evaluating Mixed-Precision Solvers,” 2020 IEEE High Performance Extreme Computing Conference (HPEC), Waltham, MA, USA, IEEE, September 2020. DOI: 10.1109/HPEC43674.2020.9286145 (1.3 MB)
Song, F., and J. Dongarra, A Scalable Framework for Heterogeneous GPU-Based Clusters,” The 24th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2012), Pittsburgh, PA, USA, ACM, June 2012.  (3.39 MB)
Ltaeif, H., S. Tomov, R. Nath, P. Du, and J. Dongarra, A Scalable High Performant Cholesky Factorization for Multicore with GPU Accelerators,” Proc. of VECPAR'10 (to appear), Berkeley, CA, June 2010.  (870.46 KB)

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