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

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.
Hoefler, T., M. Copik, P. Beckman, A. Jones, I. Foster, M. Parashar, D. Reed, M. Troyer, T. Schulthess, D. Ernst, et al., XaaS: Acceleration as a Service to Enable Productive High-Performance Cloud Computing, : arXiv, 2024-01.
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