Update Readme and CMakeLists for new git repo path

CMakeLists.txt

@@ -25,7 +25,7 @@ set(CMAKE_CUDA_USE_RESPONSE_FILE_FOR_OBJECTS 0)
 # Add Vec3  as a dependency
 include(FetchContent)
 FetchContent_Declare(Vec3
-    GIT_REPOSITORY https://www.alexselimov.com/git/aselimov/Vec3.git
+    GIT_REPOSITORY https://forge.alexselimov.com/aselimov/Vec3.git
 )
 
 FetchContent_GetProperties(Vec3)

README.md

@@ -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).