Chao Chen

Heavner, N., Chen, C., Gopal, A., & Martinsson, P. G. (2023). Efficient algorithms for computing rank‐revealing factorizations on a GPU. Numerical Linear Algebra with Applications, 30(6), e2515. https://doi.org/10.1002/nla.2515

Chen, C., & Biros, G. (2022). Overlapping Domain Decomposition Preconditioner for Integral Equations. SIAM Journal on Scientific Computing, 44(6), A3617–A3644. https://doi.org/10.1137/21m1442917

Chen, C., & Martinsson, P.-G. (2022). 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. https://doi.org/10.1109/sc41404.2022.00089

Chen, C., Reiz, S., Yu, C. D., Bungartz, H.-J., & Biros, G. (2021). Fast Approximation of the Gauss--Newton Hessian Matrix for the Multilayer Perceptron. SIAM Journal on Matrix Analysis and Applications, 42(1), 165–184. https://doi.org/10.1137/19m129961x

Wang, R., Chen, C., Lee, J., & Darve, E. (2021). PBBFMM3D: A parallel black-box algorithm for kernel matrix-vector multiplication. Journal of Parallel and Distributed Computing, 154, 64–73. https://doi.org/10.1016/j.jpdc.2021.04.005

Chen, C., Liang, T., & Biros, G. (2021). RCHOL: Randomized Cholesky Factorization for Solving SDD Linear Systems. SIAM Journal on Scientific Computing, 43(6), C411–C438. https://doi.org/10.1137/20m1380624

Boman, E. G., Cambier, L., Chen, C., Darve, E., Rajamanickam, S., & Tuminaro, R. S. (2020). A preconditioner based on sparsified nested dissection and low-rank approximation. XXI Householder Symposium on Numerical Linear Algebra, 128.

Cambier, L., Chen, C., Boman, E. G., Rajamanickam, S., Tuminaro, R. S., & Darve, E. (2020). An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations. SIAM Journal on Matrix Analysis and Applications, 41(2), 715–746. https://doi.org/10.1137/19m123806X

Takahashi, T., Chen, C., & Darve, E. (2020). Parallelization of the inverse fast multipole method with an application to boundary element method. Computer Physics Communications, 247, 106975. https://doi.org/10.1016/j.cpc.2019.106975

Lee, J., Chen, C., Toru, T., Darve, E., & Yoon, H. (2020). 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).

Chen, C., Cambier, L., Boman, E. G., Rajamanickam, S., Tuminaro, R. S., & Darve, E. (2019). A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling. Journal of Computational Physics, 396, 819–836. https://doi.org/10.1016/j.jcp.2019.07.024

Chen, C., Reiz, S., Yu, C., Bungartz, H.-J., & Biros, G. (2019). H-matrix approximation of the Gauss-Newton Hessian matrix for the multilayer perceptron. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019).

Cambier, L., Chen, C., Boman, E. G., Rajamanickam, S., Tuminaro, R. S., & Darve, E. (2019). SpaND: An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia ….

Boman, E. G., Chen, C., Darve, E., Rajamanickam, S., & Tuminaro, R. S. (2018). A Hierarchical Low-Rank Solver for Sparse Linear Systems and Its Variations. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Chen, C., Pouransari, H., Rajamanickam, S., Boman, E. G., & Darve, E. (2018). A distributed-memory hierarchical solver for general sparse linear systems. Parallel Computing, 74, 49–64. https://doi.org/10.1016/j.parco.2017.12.004

Chen, C., Tuminaro, R., Rajamanickam, S., Boman, E. G., & Darve, E. (2018). 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.

Chen, C., Tuminaro, R., Rajamanickam, S., Boman, E. G., & Darve, E. (2018). A hierarchical solver for extruded meshes with applications to ice sheet modeling. Center for Computing Research Summer Proceedings 2017, (SAND2018-2780O), 3–18.

Chen, C., Aubry, S., Oppelstrup, T., Arsenlis, A., & Darve, E. (2018). 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. https://doi.org/10.1088/1361-651x/aab7bb

Chen, C. (2018). Parallel Hierarchical Linear Solvers and Fast Multipole Methods with Applications. Stanford University.

Boman, E. G., Chen, C., & Rajamanickam, S. (2018). Scheduling Parallel Tasks using Graph Coloring. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Boman, E. G., Chen, C., Darve, E., Rajamanickam, S., & Tuminaro, R. S. (2017). A Hierarchical Low-Rank Solver for Large Sparse Linear Systems. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Boman, E. G., Chen, C., Darve, E., Rajamanickam, S., & Tuminaro, R. S. (2017). A Parallel Hierarchical Low-Rank Solver for General Sparse Matrices. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States).

Boman, E. G., Chen, C., Darve, E., Rajamanickam, S., & Tuminaro, R. S. (2017). Hierarchical Matrices and Low-Rank Methods for Extreme-Scale Solvers. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia ….

Chen, C., RAJAMANICKAM, S. I. V. A. S. A. N. K. A. R. A. N., Boman, E. G., & Darve, E. (2016). Parallel hierarchical solver for elliptic partial differential equations. CCR, 3.

Coulier, P., Chen, C., Pouransari, H., & Darve, E. (2016). 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.