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

Benoit, A., Y. Du, T. Herault, L. Marchal, G. Pallez, L. Perotin, Y. Robert, H. Sun, and F. Vivien, "Checkpointing à la Young/Daly: an overview", IC3, the 14th Int. Conf. on Contemporary Computing: ACM Press, 2022.  (639.77 KB)
Benoit, A., L. Perotin, Y. Robert, and H. Sun, "Online scheduling of moldable task graphs under common speedup models", ICPP'2022, the 50th Int. Conf. on Parallel Processing: ACM Press, 2022.  (622.81 KB)
Gao, Y., G. Pallez, Y. Robert, and F. Vivien, "Evaluating Task Dropping Strategies for Overloaded Real-Time Systems (Work-In-Progress)", 42nd Real Time Systems Symposium (RTSS): IEEE Computer Society Press, 2021.  (217.13 KB)
Benoit, A., R. Elghazi, and Y. Robert, "Max-Stretch Minimization on an Edge-Cloud Platform", IPDPS'2021, the 34th IEEE International Parallel and Distributed Processing Symposium: IEEE Computer Society Press, 2021.  (4.94 MB)
Du, Y., G. Pallez, L. Marchal, and Y. Robert, "Optimal checkpointing strategies for iterative applications", IEEE Trans. Parallel Distributed Systems, vol. 33, no. 3, pp. 507-522, 2022.  (1.47 MB)
Bathie, G., L. Marchal, Y. Robert, and S. Thibault, "Dynamic DAG scheduling under memory constraints for shared-memory platforms", Int. J. of Networking and Computing, vol. 11, no. 1, pp. 27-49, 2021.  (574.64 KB)