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

Anzt, H., T. Gruetzmacher, E. Quintana-Orti, and F. Scheidegger, "High-Performance GPU Implementation of PageRank with Reduced Precision based on Mantissa Segmentation", 8th Workshop on Irregular Applications: Architectures and Algorithms, 2018.
Anzt, H., J. Dongarra, G. Flegar, and T. Gruetzmacher, "Variable-size batched condition number calculation on GPUs", SBAC-PAD, 2018.  (509.3 KB)
Anzt, H., and J. Dongarra, "A Jaccard Weights Kernel Leveraging Independent Thread Scheduling on GPUs", SBAC-PAD, 2018.  (237.68 KB)
Tomov, S., A. Haidar, D. Schultz, and J. Dongarra, "Evaluation and Design of FFT for Distributed Accelerated Systems", ECP WBS 2.3.3.09 Milestone Report, no. FFT-ECP ST-MS-10-1216: Innovative Computing Laboratory, University of Tennessee, 10-2018.  (7.53 MB)
Bernholdt, D. E., S. Boehm, G. Bosilca, M. Grentla Venkata, R. E. Grant, T. Naughton, H. P. Pritchard, M. Schulz, and G. R. Vallee, "A Survey of MPI Usage in the US Exascale Computing Project", Concurrency Computatation: Practice and Experience, 09-2018.  (359.54 KB)
Losada, N., G. Bosilca, A. Bouteiller, P. González, and M. J. Martín, "Local Rollback for Resilient MPI Applications with Application-Level Checkpointing and Message Logging", Future Generation Computer Systems, vol. 91, pp. 450-464, 02-2019.  (1.16 MB)
Masliah, I., A. Abdelfattah, A. Haidar, S. Tomov, M. Baboulin, J. Falcou, and J. Dongarra, "Algorithms and Optimization Techniques for High-Performance Matrix-Matrix Multiplications of Very Small Matrices", Innovative Computing Laboratory Technical Report, no. ICL-UT-18-09: Innovative Computing Laboratory, University of Tennessee, 09-2018.  (3.74 MB)
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