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annayesy/README.md

Hi there 👋

I develop efficient solvers for elliptic partial differential equations (PDEs) using randomized numerical linear algebra, focusing on performance and scalability for modern heterogeneous architectures.

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  1. comp_pdes_osu comp_pdes_osu Public

    Codes for Computational PDEs I at OSU.

    Jupyter Notebook

  2. slabLU slabLU Public

    A two-level sparse direct solver for elliptic PDEs.

    Python 31

  3. skelFMM skelFMM Public

    A kernel-independent FMM without interaction lists.

    Python 3 1

  4. simpleoctree simpleoctree Public

    An adaptive 2:1 balanced tree for point distributions in 2D and 3D. Written in Python with minimal dependencies.

    Python 3