LLM training in simple, raw C/CUDA

A ML framework for the SOD2D CFD solver using SmartSim

A collection of useful .gitignore templates

高性能并行编程与优化 - 课件

music21 is a Toolkit for Computational Musicology

Codes of my MOOC Course <Play with Algorithms>, Both in C++ and Java language. Updated contents and practices are also included. 我在慕课网上的课程《算法与数据结构》示例代码，包括C++和Java版本。课程的更多更新内容及辅助练习也将逐步添加进这个代码仓。

My collection of CMake modules

Post-processing package for CFD simulations I run for my PhD

Useful CMake Examples

PyFR

Achieve a tiny STL in C++11

Simple OOP Python Code to run some Pseudo-Spectral 2D Simulations of Turbulence

A C++ FEM code sharing the same input data file with STAP90

EVTK (Export VTK) package allows exporting data to binary VTK files for visualization and data analysis

Generative Adversarial Network (GAN) for physically realistic enrichment of turbulent flow fields

Spanwise-averaged Navier–Stokes modelling through convolutional neural network

The Large-Eddy Simulation framework from the Turbulence Research Group at Johns Hopkins University

Large-eddy simulation code written in CUDA Fortran for simulating atmospheric boundary layer flows

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

DSL and compiler framework for automated finite-differences and stencil computation

code for performing active flow control of the 2D Karman street using Deep Reinforcement Learning

The public CGAL repository, see the README below

Machine learning, in numpy

MODULO (MODal mULtiscale pOd) is a software developed at the von Karman Institute to perform Multiscale Modal Analysis of numerical and experimental data using the mPOD.

VTK format using modern fortran

Basic Computational Fluid Dynamics (CFD) schemes implemented in FORTRAN using Finite-Volume and Finite-Difference Methods. Sample simulations and figures are provided.