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

Luo, X., W. Wu, G. Bosilca, Y. Pei, Q. Cao, T. Patinyasakdikul, D. Zhong, and J. Dongarra, "HAN: A Hierarchical AutotuNed Collective Communication Framework", IEEE Cluster Conference, Kobe, Japan, IEEE Computer Society Press, 2020-09.  (764.05 KB)
Abdelfattah, A., S. Tomov, and J. Dongarra, "Matrix Multiplication on Batches of Small Matrices in Half and Half-Complex Precisions", Journal of Parallel and Distributed Computing, vol. 145, pp. 188-201, 2020-11.  (1.3 MB)
Slaughter, E., W. Wu, Y. Fu, L. Brandenburg, N. Garcia, W. Kautz, E. Marx, K. S. Morris, Q. Cao, G. Bosilca, et al., "Task Bench: A Parameterized Benchmark for Evaluating Parallel Runtime Performance", Supercomputing 2020, 2020-08.  (644.92 KB)
Barry, D., A. Danalis, and H. Jagode, "Effortless Monitoring of Arithmetic Intensity with PAPI’s Counter Analysis Toolkit", 13th International Workshop on Parallel Tools for High Performance Computing, Dresden, Germany, Springer International Publishing, 2020-09.  (738.47 KB)
Brown, C., A. Abdelfattah, S. Tomov, and J. Dongarra, "Design, Optimization, and Benchmarking of Dense Linear Algebra Algorithms on AMD GPUs", Innovative Computing Laboratory Technical Report, no. ICL-UT-20-12: University of Tennessee, 2020-08.  (476.36 KB)
Dongarra, J., M. Gates, P. Luszczek, and S. Tomov, "Translational Process: Mathematical Software Perspective", Innovative Computing Laboratory Technical Report, no. ICL-UT-20-11, 2020-08.  (752.59 KB)
Archibald, R., E. Chow, E. D'Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, et al., "Integrating Deep Learning in Domain Sciences at Exascale", Innovative Computing Laboratory Technical Report, no. ICL-UT-20-10: University of Tennessee, 2020-08.  (1.09 MB)
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