Documentation Index
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What is Dedalus Conda?
Dedalus Conda provides build scripts for installing the Dedalus spectral PDE solver using Conda package management. These scripts enable flexible installation options, allowing you to use either pre-built packages from conda-forge or custom builds linked to system-specific libraries. Dedalus is a flexible framework for solving partial differential equations using modern spectral methods. It’s widely used in fluid dynamics, astrophysics, and other computational physics domains.Why Use These Build Scripts?
While Dedalus is available directly from conda-forge, the custom build scripts in this repository offer several advantages:Custom Library Support
Link to system-specific MPI, FFTW, or HDF5 libraries optimized for your cluster or workstation
Version Flexibility
Install Dedalus v2 (stable) or v3 (development) with dedicated build scripts
HPC Optimization
Configure builds for high-performance computing environments with custom MPI implementations
BLAS Options
Choose between OpenBLAS or Intel MKL for optimized linear algebra operations
Key Features
Flexible Dependency Management
The build scripts provide granular control over key dependencies:- MPI: Install OpenMPI from conda or link to custom MPI installations (MPICH, Intel MPI, etc.)
- FFTW: Use conda-forge FFTW or link to system-optimized builds
- HDF5: Choose between parallel or serial HDF5, from conda or custom installations
- BLAS: Select OpenBLAS or Intel MKL for numerical computations
Platform Support
The scripts are tested nightly via GitHub Actions on:- Linux (x86_64)
- macOS (x86_64)
- Apple Silicon (with x86_64 emulation support)
Native ARM64 builds on Apple Silicon are available but may exhibit numerical errors in some configurations. The default behavior uses x86_64 emulation via Rosetta 2.
Python Version Control
Configure the Python version for your environment (default: Python 3.12), ensuring compatibility with your existing scientific Python stack.Use Cases
Research Workstations
For laptops and individual workstations, the conda-forge installation provides the quickest path to a working Dedalus environment without requiring custom library configurations.HPC Clusters
On supercomputers and research clusters, custom build scripts allow you to:- Link to cluster-optimized MPI libraries (e.g., Cray MPICH, Intel MPI)
- Use system-installed FFTW with hardware-specific optimizations
- Integrate with parallel HDF5 builds tuned for cluster filesystems
- Match the cluster’s existing module environment
Development Environments
Developers working on Dedalus itself or building custom PDE solvers can use these scripts to:- Install development versions (v3-master branch)
- Test against different dependency configurations
- Reproduce build environments across different systems
Architecture Overview
The repository provides two main installation scripts:Dependency Installation
Install or link MPI, FFTW, HDF5, and numerical libraries based on configuration
Dedalus Installation
Build and install Dedalus from PyPI (v2) or GitHub (v3) with proper MPI linking
Threading Configuration
The build scripts automatically configure threading settings to prevent oversubscription:Next Steps
Quick Start
Get Dedalus running in minutes with the quickstart guide
Installation Methods
Compare conda-forge vs custom builds and choose the right approach