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 College of Engineering at the University of Tennessee and serves as the cornerstone laboratory of the Center for Information Technology Research (CITR), one of UT’s nine Centers of Excellence.
Recent Publications
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, 2022-03.
(5.87 MB)
Alomairy, R., M. Gates, S. Cayrols, D. Sukkari, K. Akbudak, A. YarKhan, P. Bagwell, and J. Dongarra,
"Communication Avoiding LU with Tournament Pivoting in SLATE",
SLATE Working Notes, no. 18, ICL-UT-22-01, 2022-01.
(3.74 MB)
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, 2022.
(3.19 MB)
Brown, J., A. Abdelfattah, V. Barra, N. Beams, J-S. Camier, V. Dobrev, Y. Dudouit, L. Ghaffari, T. Kolev, D. Medina, et al.,
"libCEED: Fast algebra for high-order element-based discretizations",
Journal of Open Source Software, vol. 6, no. 63, pp. 2945, 2021.
Abdelfattah, A., V. Barra, N. Beams, R. Bleile, J. Brown, J-S. Camier, R. Carson, N. Chalmers, V. Dobrev, Y. Dudouit, et al.,
"GPU algorithms for Efficient Exascale Discretizations",
Parallel Computing, vol. 108, pp. 102841, 2021.