Лабораторные работы по курсу "Технология параллельных вычислений"
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Updated
Jul 27, 2018 - C++
Лабораторные работы по курсу "Технология параллельных вычислений"
This is the calculation program of quasi-periodic Green's function for the Helmholtz equations. The quasi-periodicity is 1-dimension ( x component only ), Green's function is 2-dimensions.
simulate/reconstruction for rays through Helmholtz equation's Hamiltonian and scattered by reflective scatters (julia v0.6).
Laboratory works on the course "Parallel Computing Technologies "
imaging point sources
Solves Helmholtz equation with any kind of initial and boundary conditions using MPI.
Spectrally accurate hybrid direct solver for frequency domain scattering
This is the calculation program of quasi-periodic Green's function for the Helmholtz equations. The quasi-periodicity is 1-dimension ( x component only ), Green's function is 3-dimensions.
Computes eigen frequencies in a 1D micro-cavity
Efficient methods for computing Quasi-Periodic Green Functions for the 2D Helmholtz equation
collection of thermodynamic models, using ThermoState.jl
Численное решение неоднородного двумерного уравнения Гельмгольца (стационарное распределение температуры) с помощью технологии параллельных вычислений MPI с распределенной памятью. Для решения системы линейных алгебраических уравнений используются методы Якоби и Зейделя
Solves Helmholtz equation with Jacoby and red-black i Iterative methods.
Reference implementation of Jacobi & Seidel iteration for Helmholtz equation using MPI concurrency
This repository implements the frequency-domain adapt-then-combine full waveform inversion in Python, a fully distributed version of the FWI suited for seismic networks.
FEniCS implementation of the numerical method introduced in the paper E. Burman, M. Nechita and L. Oksanen, Unique continuation for the Helmholtz equation using stabilized finite element methods, J. Math. Pures Appl., 2019.
Acoustic scattering from multiple n-spheres in NumPy / PyTorch
The Helmholtz Method: Using Perceptual Compression to Reduce Machine Learning Complexity
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