DSL and compiler framework for automated finite-differences and stencil computation
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Updated
Jun 28, 2024 - Python
DSL and compiler framework for automated finite-differences and stencil computation
An adaptive and distributed-memory parallel implementation of the immersed boundary (IB) method
C and Python examples from my book on using PETSc and Firedrake to solve PDEs
Basic Computational Fluid Dynamics (CFD) schemes implemented in FORTRAN using Finite-Volume and Finite-Difference Methods. Sample simulations and figures are provided.
Code for geophysical 3D/2D Finite Difference modelling, Marchenko algorithms, 2D/3D x-w migration and utilities.
Python package for numerical derivatives and partial differential equations in any number of dimensions.
My personal collection of Riemann solvers using MUSCL and WENO schemes written as short Matlab scripts
Discretization tools for finite volume and inverse problems.
Domain-specific compiler and code transformation system for Finite Difference/Volume/Element Earth-system models in Fortran
Collection of codes in Matlab(R) and C++ for solving basic problems presented and discussed in the "Computational Fluid Dynamics of Reactive Flows" course (Politecnico di Milano)
These matlab codes simulate grain growth by solving the phase field equations using a centered finite difference method
Encoding physics to learn reaction-diffusion processes
Pure Python implementation of the finite difference frequency domain (FDFD) method for electromagnetics
Solving Schrodinger Equation Numerically
Finite difference solution of 2D Poisson equation. Can handle Dirichlet, Neumann and mixed boundary conditions.
A Julia library of summation-by-parts (SBP) operators used in finite difference, Fourier pseudospectral, continuous Galerkin, and discontinuous Galerkin methods to get provably stable semidiscretizations, paying special attention to boundary conditions.
🌀 Selected MATLAB code I wrote while taking a CFD class in graduate school. Finite-difference and finite volume approximations are compared to analytical solutions. Project descriptions are included. 🌀
Acoustic wave propagation in 2D domain using CUDA, O(2,8). Solve second order wave equation in time domain using finite-differences.
GPU-comcot offloads the computational component on the outermost layer of COMCOT to Nvidia GPU. Currently, the speed up achieved by parallelized code on GTX-1060 comparing to serial one on AMD-FX8150 is nearly 200X. The code is still under development to fulfill the full functionality of the original model.
A Physics-Informed Neural Network to solve 2D steady-state heat equations.
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