Lightweight, general, scalable C++ library for finite element methods
- finite-elements
- high-order
- high-performance-computing
- parallel-computing
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Lightweight, general, scalable C++ library for finite element methods
Kratos Multiphysics (A.K.A Kratos) is a framework for building parallel multi-disciplinary simulation software. Modularity, extensibility and HPC are the main objectives. Kratos has BSD license and is written in C++ with extensive Python interface.
Official Repository for the Uni-Mol Series Methods
C++ library for solving large sparse linear systems with algebraic multigrid method
QuadriFlow: A Scalable and Robust Method for Quadrangulation
Parallel solvers for sparse linear systems featuring multigrid methods.
libMesh github repository
A flexible framework for solving PDEs with modern spectral methods.
Firedrake is an automated system for the portable solution of partial differential equations using the finite element method (FEM)
Numerical linear algebra software package
A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
A Python native dynamical system simulation framework in the block diagram paradigm.
High performance computational platform in Python for the spectral Galerkin method
Umbrella package of the 'spatstat' family................
An automatic code generator for nonlinear model predictive control (NMPC) and the continuation/GMRES method (C/GMRES) based numerical solvers for NMPC
A framework for high-performance domain decomposition methods.
:dart: Accurate sums and dot products for Python.
High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations
Methods for Image-Based Cell Profiling
A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration Resources
A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders
A metaheuristic optimization framework
DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.