Update Readme and CMakeLists for new git repo path

This commit is contained in:
Alex Selimov 2025-08-25 20:51:12 -04:00
parent 746face829
commit cad74747bf
Signed by: aselimov
GPG key ID: 3DDB9C3E023F1F31
2 changed files with 34 additions and 11 deletions

View file

@ -1,12 +1,35 @@
# C++ Project Template
When setting out on a new project in C++ there are a few configuration steps
which need to be completed prior to actually getting down to writing code.
This repository is going to be a C++ project template that already has the
following components:
# ⚛️ CudaCAC
- Directory Structure
- Make Build (CMake)
- CUDA integration
- Unit Test Framework (Google Test)
- API Documentation (Doxygen)
CudaCAC is a Cuda accelerated implementation of the Concurrent Atomistic-Continuum (CAC) method.
## Background
### Molecular Dynamics
Molecular dynamics (MD) is a computer simulation method for analyzing the physical movements of atoms and molecules. The atoms and molecules are allowed to interact for a fixed period of time, giving a view of the dynamic evolution of the system. In the most common version, the trajectories of atoms and molecules are determined by numerically solving Newton's equations of motion for a system of interacting particles, where forces between the particles and their potential energies are often calculated using interatomic potentials or molecular mechanics force fields.
### Concurrent Atomistic-Continuum (CAC) Method
The Concurrent Atomistic-Continuum (CAC) method is a multiscale modeling technique used for simulating materials at the nano and micro-scale. It partitions a simulation into a coarse-grained domain and an atomistic domain. This allows for the detailed, fully-resolved atomistic simulation of important regions, like those with lattice defects, while more efficiently modeling the rest of the material as a continuum. A key feature of the CAC method is its use of a unified set of governing equations and interatomic potentials across both the atomistic and continuum domains. This avoids the need for complex coupling procedures at the interface of the two regions.
## Tech Stack
This project leverages a high-performance computing stack for its simulations:
* **C++:** The core application logic is written in modern C++, providing a balance of performance and high-level abstractions.
* **CUDA:** NVIDIA's CUDA platform is used to accelerate the computationally intensive parts of the simulation on the GPU.
* **CMake:** A cross-platform build system used to manage the compilation and linking of the project.
* **Google Test:** A testing framework for writing C++ tests.
* **Doxygen:** A documentation generator for C++ code.
## Roadmap
- [ ] Complete basic molecular dynamics atomistic solver using Cuda using Lennard-Jones pair potential with order O(n^2) calculations
- [ ] Implement CAC rhombohedral finite element solver
- [ ] Adding neighbor lists with cutoff distances to reduce runtime complexity
- [ ] Adding multi-body potential support
- [ ] Adding support for overlaying multiple potentials
## Contact
For any questions or inquiries, please contact Alex Selimov at [alex@alexselimov.com](mailto:alex@alexselimov.com) or visit his website at [alexselimov.com](https://alexselimov.com).