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Making root cause analysis feasible for large code bases: a solution approach for a climate model., , , , , и . CoRR, (2018)Scaling Algebraic Multigrid Solvers: On the Road to Exascale., , , , , и . CHPC, стр. 215-226. Springer, (2010)Toward Memory-Efficient Linear Solvers., , и . VECPAR, том 2565 из Lecture Notes in Computer Science, стр. 315-327. Springer, (2002)On Preserving Scientific Integrity for Climate Model Data in the HPC Era.. Comput. Sci. Eng., 23 (6): 16-24 (2021)A scalable eigensolver for large scale-free graphs using 2D graph partitioning., , , и . SC, стр. 63:1-63:11. ACM, (2011)Assessing Differences in Large Spatio-temporal Climate Datasets with a New Python package., , и . IEEE BigData, стр. 2699-2707. IEEE, (2020)Improving algebraic multigrid interpolation operators for linear elasticity problems., , и . Numer. Linear Algebra Appl., 17 (2-3): 495-517 (2010)Scalability of Classical Algebraic Multigrid for Elasticity to Half a Million Parallel Tasks., , , , , и . Software for Exascale Computing, том 113 из Lecture Notes in Computational Science and Engineering, Springer, (2016)An efficient parallel termination detection algorithm., , и . IJPEDS, 21 (4): 293-301 (2006)Towards Characterizing the Variability of Statistically Consistent Community Earth System Model Simulations., , , , , и . ICCS, том 80 из Procedia Computer Science, стр. 1589-1600. Elsevier, (2016)