Chao Chen

Overlapping Domain Decomposition Preconditioner for Integral Equations

SIAM Journal on Scientific Computing, 44(6), A3617–A3644.

Solving linear systems on a GPU with hierarchically off-diagonal low-rank approximations

SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, 1–15.

Efficient algorithms for computing rank-revealing factorizations on a GPU

Numerical Linear Algebra with Applications, e2515.

Fast approximation of the Gauss--Newton Hessian matrix for the multilayer perceptron

SIAM Journal on Matrix Analysis and Applications, 42(1), 165–184.

PBBFMM3D: a parallel black-box algorithm for kernel matrix-vector multiplication

Journal of Parallel and Distributed Computing, 154, 64–73.

RCHOL: Randomized Cholesky factorization for solving SDD linear systems

SIAM Journal on Scientific Computing, 43(6), C411–C438.

A preconditioner based on sparsified nested dissection and low-rank approximation

XXI Householder Symposium on Numerical Linear Algebra, 128.

An algebraic sparsified nested dissection algorithm using low-rank approximations

SIAM Journal on Matrix Analysis and Applications, 41(2), 715–746.

Parallelization of the inverse fast multipole method with an application to boundary element method

Computer Physics Communications, 247, 106975.

Scalable spatio-temporal modeling using a fast multipole method for 3D tracer concentration breakthrough data with magnetic resonance imaging.

Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling

Journal of Computational Physics, 396, 819–836.

H-matrix approximation of the Gauss-Newton Hessian matrix for the multilayer perceptron

33rd Conference on Neural Information Processing Systems (NeurIPS 2019).

SpaND: An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations.

Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia ….

A Hierarchical Low-Rank Solver for Sparse Linear Systems and Its Variations.

Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

A distributed-memory hierarchical solver for general sparse linear systems

Parallel Computing, 74, 49–64.

A hierarchical solver for extruded meshes with applications to ice sheet modeling

In A. D. Baczewski & M. L. Parks (Eds.), Center for Computing Research Summer Proceedings 2017 (Technical Report No. SAND2018-2780O; pp. 3–18). Sandia National Laboratories.

Fast algorithms for evaluating the stress field of dislocation lines in anisotropic elastic media

Modelling and Simulation in Materials Science and Engineering, 26(4), 045007.

Parallel Hierarchical Linear Solvers and Fast Multipole Methods with Applications

Stanford University.

Scheduling Parallel Tasks using Graph Coloring.

Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

A Hierarchical Low-Rank Solver for Large Sparse Linear Systems.

Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

A Parallel Hierarchical Low-Rank Solver for General Sparse Matrices.

Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Hierarchical Matrices and Low-Rank Methods for Extreme-Scale Solvers.

Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia ….

Parallel hierarchical solver for elliptic partial differential equations

In J. B. Carleton & M. L. Parks (Eds.), Center for Computing Research Summer Proceedings 2016 (Technical Report No. SAND2017-1294R; pp. 3–16). Sandia National Laboratories.

Parallel hierarchical solver for elliptic partial differential equations

CCR, 3.

The Inverse Fast Multipole Method as an Efficient Preconditioner for Dense Linear Systems

Conference on Parallel Processing for Scientific Computing, Date: 2016/04/12-2016/04/15, Location: Paris, France.