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., A. Cavelan, F. Cappello, P. Raghavan, Y. Robert, and H. Sun, "Coping with silent and fail-stop errors at scale by combining replication and checkpointing", J. Parallel and Distributed Computing, vol. to appear, 2018.  (837 KB)
Aupy, G., A. Benoit, B. Goglin, L. Pottier, and Y. Robert, "Co-scheduling HPC workloads on cache-partitioned CMP platforms", Cluster'2018: IEEE Computer Society Press, 2018.  (423.75 KB)
Benoit, A., S. Perarnau, L. Pottier, and Y. Robert, "A performance model to execute workflows on high-bandwidth memory architectures", ICPP'2018, the 47th Int. Conf. on Parallel Processing: IEEE Computer Society Press, 2018.  (868.44 KB)
Han, L., V. Le Fèvre, L-C. Canon, Y. Robert, and F. Vivien, "A Generic Approach to Scheduling and Checkpointing Workflows", ICPP'2018, the 47th Int. Conf. on Parallel Processing: IEEE Computer Society Press, 2018.  (737.11 KB)
Le Fèvre, V., G. Bosilca, A. Bouteiller, T. Herault, A. Hori, Y. Robert, and J. Dongarra, "Do moldable applications perform better on failure-prone HPC platforms?", Resilience: 11th Workshop on Resiliency in High Performance Computing in Clusters, Clouds, and Grids, jointly published with Euro-Par 2018: Springer Verlag, 2018.  (360.72 KB)
Beck, M., T. Moore, and P. Luszczek, "Interoperable Convergence of Storage, Networking, and Computation", Future of Information and Communication Conference (FICC), San Francisco, Science and Information (SAI), 03-2019.  (1.8 MB)
Jagode, H., A. Danalis, and J. Dongarra, "Accelerating NWChem Coupled Cluster through dataflow-based Execution", The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 540--551, 07-2018.  (1.68 MB)
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