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

Haidar, A., H. Jagode, P. Vaccaro, A. YarKhan, S. Tomov, and J. Dongarra, "Investigating power capping toward energy-efficient scientific applications", Concurrency Computatation: Practice and Experience, vol. 2018, issue e4485, 04-2018.  (1.2 MB)
Aupy, G., A. Benoit, S. Dai, L. Pottier, P. Raghavan, Y. Robert, and M. Shantharam, "Co-scheduling Amdhal applications on cache-partitioned systems", Int. Journal of High Performance Computing Applications, vol. 32, no. 1, pp. 123-138, 2018.  (672.52 KB)
Caniou, Y., E. Caron, A. Kong Win Chang, and Y. Robert, "Budget-aware scheduling algorithms for scientific workflows with stochastic task weights on heterogeneous IaaS cloud platforms", 27th International Heterogeneity in Computing Workshop {HCW 2013}: IEEE Computer Society Press, 2018.  (1.31 MB)
Herault, T., Y. Robert, A. Bouteiller, D. Arnold, K. Ferreira, G. Bosilca, and J. Dongarra, "Optimal Cooperative Checkpointing for Shared High-Performance Computing Platforms", APDCM workshop (co-located with IPDPS), Vancouver, BC, Canada, IEEE, 05-2018.  (899.3 KB)
Yamazaki, I., A. Abdelfattah, A. Ida, S. Ohshima, S. Tomov, R. Yokota, and J. Dongarra, "Analyzing Performance of BiCGStab with Hierarchical Matrix on GPU clusters", IEEE International Parallel and Distributed Processing (IPDPS) Symposium, 2018.
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