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Robust and Accurate Stopping Criteria for Adaptive Randomized Sampling in Matrix-Free Hierarchically Semiseparable Construction.

, , , , , and . SIAM J. Sci. Comput., 41 (5): S61-S85 (2019)

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The Impact of Global Communication Latency at Extreme Scales on Krylov Methods., , , and . ICA3PP (1), volume 7439 of Lecture Notes in Computer Science, page 428-442. Springer, (2012)Hiding Global Communication Latency in the GMRES Algorithm on Massively Parallel Machines., , , and . SIAM J. Sci. Comput., (2013)Butterfly factorization via randomized matrix-vector multiplications., , , , , and . CoRR, (2020)A multi-level preconditioned Krylov method for the efficient solution of algebraic tomographic reconstruction problems., , , , and . J. Comput. Appl. Math., (2015)Using Fast and Accurate Simulation to Explore Hardware/Software Trade-offs in the Multi-Core Era., , , , , and . PARCO, volume 22 of Advances in Parallel Computing, page 343-350. IOS Press, (2011)Sparse Approximate Multifrontal Factorization with Composite Compression Methods., , , , , , and . ACM Trans. Math. Softw., 49 (3): 24:1-24:28 (September 2023)Deep Learning and Spectral Embedding for Graph Partitioning., , , , and . PPSC, page 25-36. SIAM, (2022)Scalable and Memory-Efficient Kernel Ridge Regression., , , , and . IPDPS, page 956-965. IEEE, (2020)Hiding global synchronization latency in the preconditioned Conjugate Gradient algorithm., and . Parallel Comput., 40 (7): 224-238 (2014)Improving strong scaling of the Conjugate Gradient method for solving large linear systems using global reduction pipelining., , , and . CoRR, (2019)