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

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)
Asch, M., T. Moore, R. M. Badia, M. Beck, P. Beckman, T. Bidot, F. Bodin, F. Cappello, A. Choudhary, B. R. de Supinski, et al., "Big Data and Extreme-Scale Computing: Pathways to Convergence - Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry", The International Journal of High Performance Computing Applications, vol. 32, issue 4, pp. 435–479, 07-2018.  (1.29 MB)
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, "Optimizing GPU Kernels for Irregular Batch Workloads: A Case Study for Cholesky Factorization", IEEE High Performance Extreme Computing Conference (HPEC’18), Waltham, MA, IEEE, 09-2018.
Abdelfattah, A., A. Haidar, S. Tomov, and J. Dongarra, "Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures", Journal of Computational Science, vol. 26, pp. 226–236, 05-2018.  (3.73 MB)
Haidar, A., A. Abdelfattah, M. Zounon, S. Tomov, and J. Dongarra, "A Guide for Achieving High Performance with Very Small Matrices on GPU: A Case Study of Batched LU and Cholesky Factorizations", IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 5, pp. 973–984, 05-2018.  (832.92 KB)
YarKhan, A., G. Ragghianti, J. Dongarra, M. Cawkwell, D. Perez, and A. Voter, "Initial Integration and Evaluation of SLATE Parallel BLAS in LATTE", Innovative Computing Laboratory Technical Report, no. ICL-UT-18-07: Innovative Computing Laboratory, University of Tennessee, 06-2018.  (366.6 KB)
Kurzak, J., M. Gates, A. YarKhan, I. Yamazaki, P. Luszczek, J. Finney, and J. Dongarra, "Parallel Norms Performance Report", SLATE Working Notes, no. 6, ICL-UT-18-06: Innovative Computing Laboratory, University of Tennessee, 06-2018.  (1.13 MB)
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