637 Open source projects that are alternatives of or similar to Feelpp

Lightweight, general, scalable C++ library for finite element methods

Python wrapper for MFEM

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SUNDIALS is a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. This is a mirror of current releases, and development will move here eventually. Pull requests are welcome for bug fixes and minor changes.

Netgen/NGSolve is a high performance multiphysics finite element software. It is widely used to analyze models from solid mechanics, fluid dynamics and electromagnetics. Due to its flexible Python interface new physical equations and solution algorithms can be implemented easily.

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A parallel application binary interface for Fortran 2018 compilers.

Parallel Workflow extension for Rake, runs on multicores, clusters, clouds.

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C and Python examples from my book on using PETSc to solve PDEs

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Extreme-scale Discontinuous Galerkin Environment (EDGE)

libMesh github repository

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Massively parallel FEM code for phase-field for fracture by Dolbow Lab at Duke University

podgorskiy.com/spblog/304/writing-a-fem-solver-in-less-the-180-lines-of-code

Efficient Matlab Implementation of Adaptive Mesh Refinement in 2D

Multi-threaded Optimization Toolbox

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Open source library for scientific HPC

A framework for Smoothed Particle Hydrodynamics in Python

Structured Adaptive Mesh Refinement Application Infrastructure - a scalable C++ framework for block-structured AMR application development

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NASOQ:Numerically Accurate Sparsity Oriented QP Solver

OpenCL integration for Python, plus shiny features

The nutils project

A Clojure dataframe library that runs on Spark

A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

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BriefFiniteElementDotNET (BFE.NET) is a library for linear-static Finite Element Method (FEM) analysis of solids and structures in .NET

A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures.

A suite of benchmarks to test the sequential CPU and GPU performance of most popular high-performance libraries for Python.

Fast and easy parallel mapreduce on HPC clusters

Fast, Expressive, & High-Performance Programming Language for those who dare

parallel finite element unstructured meshes

Tools for computation on batch systems

Parallel algorithms and data structures for tree-based AMR with arbitrary element shapes.

Topology optimization using PETSc: a Python wrapper and extended functionality

GraphIt - A High-Performance Domain Specific Language for Graph Analytics

An easy to follow library to make Fortran easier in general with wrapped interfaces, sorting routines, kD-Trees, and other algorithms to handle scientific data and concepts. The library contains core fortran routines and object-oriented classes.

DASH, the C++ Template Library for Distributed Data Structures with Support for Hierarchical Locality for HPC and Data-Driven Science

Advanced Simulation Library - hardware accelerated multiphysics simulation platform.

Sequential model-based optimization with a `scipy.optimize` interface

Grid-based approximation of partial differential equations in Julia

PHP library for scientific computing powered by C

Computator.NET is a special kind of numerical software that is fast and easy to use but not worse than others feature-wise. It's features include: - Real and complex functions charts - Real and complex calculator - Real functions numerical calculations including different methods - Over 107 Elementary functions - Over 141 Special functions - Over 21 Matrix functions and operations - Scripting language with power to easy computations including matrices - You can declare your own custom functions with scripting language

Image-processing software for cryo-electron microscopy

High-performance object-based library for DLA computations

Download videos using youtube-dl and upload to the Internet Archive with metadata.

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Matplot++: A C++ Graphics Library for Data Visualization 📊🗾

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Must read research papers and links to tools and datasets that are related to using machine learning for compilers and systems optimisation