This guide documents how to install and run the MFEM examples using Spack.
Tested on MacOS (Apple Silicon) with MPI.
| use rayon::prelude::*; | |
| pub struct Particles { | |
| /// Total number of particles in the simulation. | |
| pub n: usize, | |
| pub x: Vec<f64>, | |
| pub u: Vec<f64>, | |
| pub f: Vec<f64>, | |
| /// Mass of particles. |
| # User specific environment | |
| if ! [[ "$PATH" =~ "$HOME/.local/bin:$HOME/bin:" ]]; then | |
| PATH="$HOME/.local/bin:$HOME/bin:$PATH" | |
| fi | |
| export PATH | |
| # Uncomment the following line if you don't like systemctl's auto-paging feature: | |
| # export SYSTEMD_PAGER= |
| /* | |
| ***************************************************** | |
| ***************************************************** | |
| ***************************************************** | |
| *** O O O O O O O O O O O O O O O O O O O O O O O *** | |
| *** O O O O O O O O O O O O O O O O O O O O O O O *** | |
| *** O O O O O O O O O O O O O O O O O O O O O O O *** | |
| *** O O O O O O O O O O O O O O O O O O O O O O O *** | |
| *** O O O O O O O O O O O O O O O O O O O O O O O *** |
To effectively learn Neural Networks, it’s best to build your understanding step-by-step, starting from foundational concepts in math and programming, and progressing through machine learning. Here's a clear learning path:
Install pysph
pip install 'cython<3'
pip install 'numpy==1.23'
pip install h5py
pip install https://github.com/pypr/pysph/zipball/master| # Define the build directory containing binaries | |
| BUILD_DIR := /home/dineshadepu/life/softwares/Cabana_package_template/build | |
| # for mac os | |
| BUILD_DIR := /Users/dineshadepu/life/softwares/Cabana_package_template/build | |
| # Find all binaries in BUILD_DIR with "test" in the name (Ubuntu compatible) | |
| TEST_BINARIES := $(shell find $(BUILD_DIR) -type f -executable -name "*test*") | |
| # for mac os | |
| # TEST_BINARIES := $(shell find $(BUILD_DIR) -type f -perm +111 -name "*test*") |