6 papers
Adaptive, Matrix-Free Low-Rank Approximation
Arnel I. Smith, Elly Do, Chao Chen
We study fixed-tolerance low-rank approximation in the matrix-free setting, where a matrix or linear operator is accessible only through matrix-vector products and its…
A High-Throughput GPU Framework for Adaptive Lossless Compression of Floating-Point Data
Zheng Li, Weiyan Wang, Ruiyuan Li +5
The torrential influx of floating-point data from domains like IoT and HPC necessitates high-performance lossless compression to mitigate storage costs while preserving absolute da…
Parametric Hierarchical Matrix Approximations to Kernel Matrices
Abraham Khan, Chao Chen, Vishwas Rao +1
Kernel matrices are ubiquitous in computational mathematics, often arising from applications in machine learning and scientific computing. In two or three spatial or feature dimens…
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…
Parallel GPU-Accelerated Randomized Construction of Approximate Cholesky Preconditioners
Tianyu Liang, Chao Chen, Yotam Yaniv +5
We introduce a parallel algorithm to construct a preconditioner for solving a large, sparse linear system where the coefficient matrix is a Laplacian matrix (a.k.a., graph Laplacia…
Robust Blockwise Random Pivoting: Fast and Accurate Adaptive Interpolative Decomposition
Yijun Dong, Chao Chen, Per-Gunnar Martinsson +1
The interpolative decomposition (ID) aims to construct a low-rank approximation formed by a basis consisting of row/column skeletons in the original matrix and a corresponding inte…