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

Castain, R., J. Hursey, A. Bouteiller, and D. Solt, "PMIx: Process Management for Exascale Environments", Parallel Computing, vol. 79, pp. 9–29, 01-2018.
Anzt, H., E. Chow, and J. Dongarra, "ParILUT–-A New Parallel Threshold ILU Factorization", SIAM Journal on Scientific Computing, vol. 40, no. 4, pp. C503–C519, 2018.  (469.24 KB)
Chow, E., H. Anzt, J. Scott, and J. Dongarra, "Using Jacobi iterations and blocking for solving sparse triangular systems in incomplete factorization preconditioning", Journal of Parallel and Distributed Computing, vol. 119, pp. 219–230, 2018.  (273.53 KB)
Anzt, H., J. Dongarra, G. Flegar, and E. S. Quintana-Ortí, "Variable-size batched Gauss–Jordan elimination for block-Jacobi preconditioning on graphics processors", Parallel Computing, 2018.  (1.9 MB)
Anzt, H., M. Kreutzer, E. Ponce, G. D. Peterson, G. Wellein, and J. Dongarra, "Optimization and performance evaluation of the IDR iterative Krylov solver on GPUs", The International Journal of High Performance Computing Applications, vol. 32, no. 2, pp. 220–230, 2018.  (2.08 MB)
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)
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