Enabling technologies and software for scientific computing

The Innovative Computing Laboratory (ICL) aspires to be a world leader in enabling technologies and software for scientific computing. Our vision is to provide high performance tools to tackle science’s most challenging problems and to play a major role in the development of standards for scientific computing in general.

ICL is a research laboratory in the Department of Electrical Engineering and Computer Science in the Tickle College of Engineering at the University of Tennessee.

Recent Publications

Dongarra, J., and D. Keyes, "The co-evolution of computational physics and high-performance computing", Nature Reviews Physics, 2024-08.
Bautista-Gomez, L., A. Benoit, S. Di, T. Herault, Y. Robert, and H. Sun, "A survey on checkpointing strategies: Should we always checkpoint à la Young/Daly?", Future Generation Computer Systems, 2024-07.
Kovalchuk, S. V., C. de Mulatier, V. V. Krzhizhanovskaya, J. Mikyška, M. Paszyński, J. Dongarra, and P. M. A. Sloot, "Computation at the Cutting Edge of Science", Journal of Computational Science, 2024-06.
Luszczek, P., A. Abdelfattah, H. Anzt, A. Suzuki, and S. Tomov, "Batched sparse and mixed-precision linear algebra interface for efficient use of GPU hardware accelerators in scientific applications", Future Generation Computer Systems, vol. 160, pp. 359 - 374, 2024-11.
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, 2024-04.
Melnichenko, M., O. Balabanov, R. Murray, J. Demmel, M. W. Mahoney, and P. Luszczek, CholeskyQR with Randomization and Pivoting for Tall Matrices (CQRRPT), : arXiv, 2024-02.
Lindquist, N., P. Luszczek, and J. Dongarra, Generalizing Random Butterfly Transforms to Arbitrary Matrix Sizes, : arXiv, 2023-12.
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