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

Tsai, Y. M., T. Cojean, and H. Anzt, "Sparse Linear Algebra on AMD and NVIDIA GPUs—The Race is On", ISC High Performance: Springer, 2020-06.  (5.63 MB)
Anzt, H., T. Cojean, C. Yen-Chen, J. Dongarra, G. Flegar, P. Nayak, S. Tomov, Y. M. Tsai, and W. Wang, "Load-Balancing Sparse Matrix Vector Product Kernels on GPUs", ACM Transactions on Parallel Computing, vol. 7, issue 1, 2020-03.  (5.67 MB)
Anzt, H., T. Cojean, Y-C. Chen, F. Goebel, T. Gruetzmacher, P. Nayak, T. Ribizel, and Y-H. Tsai, "Ginkgo: A High Performance Numerical Linear Algebra Library", Journal of Open Source Software, vol. 5, issue 52, 2020-08.  (721.84 KB)
Goebel, F., H. Anzt, T. Cojean, G. Flegar, and E. S. Quintana-Orti, "Multiprecision Block-Jacobi for Iterative Triangular Solves", European Conference on Parallel Processing (Euro-Par 2020): Springer, 2020-08.
YarKhan, A., M. Al Farhan, D. Sukkari, M. Gates, and J. Dongarra, SLATE Performance Report: Updates to Cholesky and LU Factorizations, , 2020.  (1.64 MB)
Zhong, D., Q. Cao, G. Bosilca, and J. Dongarra, "Using Advanced Vector Extensions AVX-512 for MPI Reduction", EuroMPI 2020, Austin, TX, 2020-09.  (634.45 KB)
Brown, C., A. Abdelfattah, S. Tomov, and J. Dongarra, "Design, Optimization, and Benchmarking of Dense Linear Algebra Algorithms on AMD GPUs", 2020 IEEE High Performance Extreme Computing Virtual Conference: IEEE, 2020-09.  (476.36 KB)
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