7 papers
Randomized Block Low-Rank Matrix Compression by Tagging
Katherine J. Pearce, Anna Yesypenko, James Levitt +1
In this work, we present randomized compression algorithms for flat rank-structured matrices with shared bases, termed uniform Block Low-Rank (BLR) matrices. Our main contribution…
Randomized Strong Recursive Skeletonization: Simultaneous Compression and LU Factorization of Hierarchical Matrices using Matrix-Vector Products
Anna Yesypenko, Per-Gunnar Martinsson
The hierarchical matrix framework partitions matrices into subblocks that are either small or of low numerical rank, enabling linear storage complexity and efficient matrix-vector…
An overlapping domain decomposition method based on solution-transfer operators
Simon Dirckx, Anna Yesypenko, Per-Gunnar Martinsson
An overlapping domain decomposition method is described for variable-coefficient elliptic boundary value problems on domains that can be decomposed into slabs or shells. The method…
A Two-Level Direct Solver for the Hierarchical Poincaré-Steklov Method
Joseph Kump, Anna Yesypenko, Per-Gunnar Martinsson
We introduce a two-level direct solver for the Hierarchical Poincaré-Steklov (HPS) method for solving linear elliptic PDEs. HPS combines multidomain spectral collocation with a di…
SlabLU: A Two-Level Sparse Direct Solver for Elliptic PDEs
Anna Yesypenko, Per-Gunnar Martinsson
The paper describes a sparse direct solver for the linear systems that arise from the discretization of an elliptic PDE on a two dimensional domain. The scheme decomposes the domai…
A Simplified Fast Multipole Method Based on Strong Recursive Skeletonization
Anna Yesypenko, Chao Chen, Per-Gunnar Martinsson
This work introduces a kernel-independent, multilevel, adaptive algorithm for efficiently evaluating a discrete convolution kernel with a given source distribution. The method is b…