https://github.com/sbstndb/samurai_spack
Spack recipe for Samurai AMR software based on the xtensor stack
https://github.com/sbstndb/samurai_spack
samurai spack xtensor
Last synced: 2 months ago
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Spack recipe for Samurai AMR software based on the xtensor stack
- Host: GitHub
- URL: https://github.com/sbstndb/samurai_spack
- Owner: sbstndb
- Created: 2024-11-05T14:38:13.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-02-21T15:58:01.000Z (3 months ago)
- Last Synced: 2025-02-21T16:29:20.080Z (3 months ago)
- Topics: samurai, spack, xtensor
- Language: Python
- Homepage:
- Size: 53.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Spack Recipe for Samurai
This repository contains spack recipes for installing [`Samurai`](https://github.com/hpc-maths/samurai), a High-Performance Computation mesh library.
# Prequisities
Before guietting started, ensure that Spack is intalled on your system. Follow the [official Spack documentation](https://spack.io/) for detailed installation instructions.
# Installation steps
1. Clone this repository
Clone the repository to a directory of your choice:
```bash
git clone [email protected]:hpc-maths/spack_samurai.git
cd spack_samurai
```
2. Add the repository to Spack
Add the repository to your local Spack setup :
```bash
spack repo add .
```
3. Explore available options
Display information about the Samurai recipe and its configuration options:
```bash
spack info samurai
```
4. Install `Samurai`
To install with default options (recommanded), run:
```bash
spack install samurai
```
For advanced users, you can specify build options or dependencies. For example:
For example:
```bash
spack install samurai +openmp +demos %[email protected]
```
# Usage
5. Load Samurai
After installation, load the Samurai module into your environment:
```bash
spack load samurai
```
6. Unload Samurai:
To unload Samurai module from your environment, use:
```bash
spack unload samurai
```