v0.5.2: including Vela.jl

Vela.jl included as well

Alpha version, fully functional

There were pre-alpha bugs in permission and user handling. These have all been fixed now. We have two versions per target architecture: singularity and plain (e.g. cpu-singularity and cpu). The devcontainer.json has been tested.

Release v0.4.0: consolidated images

Changes:

• consolidated images for docker and devcontainer use. Much more robust approach to permissions and users
• updated psrcat (was silently not building)
• updated psrchive (was not detecting healpix)

Release v0.3.0: updated users/permissions management

Overhauled the way users and permissions are handled. We now have three targets for all versions: singularity, devcontainer, and plain, each for cpu, cuda124, cuda128, and cuda13

Release v0.2.1: updated devcontainer.json

This is just an update to the devcontainer. The Dockerhub images are the same (just use v0.2.0)

The devcontainer setup was convoluted, and caused errors with permissions. Now, with this updated approach, we only need a devcontainer.json, and all permissions are handled properly

Release v0.2.0

Release v0.2.0

🎉 Major Updates

This release expands GPU support with three CUDA variants and updates the entire software stack to the latest versions.

🆕 New Features

Expanded GPU Support

• Added CUDA 12.8 variant (Ubuntu 24.04) with PyTorch 2.9.0 and JAX 0.8.0
• Added CUDA 13 variant (Ubuntu 24.04) with PyTorch 2.9.0 and JAX 0.8.0
• Now providing 8 container variants total (up from 4):
  • CPU (Docker & Singularity) - Ubuntu 24.04
  • GPU CUDA 12.4 (Docker & Singularity) - Ubuntu 22.04
  • GPU CUDA 12.8 (Docker & Singularity) - Ubuntu 24.04
  • GPU CUDA 13 (Docker & Singularity) - Ubuntu 24.04

Base Image Updates

• CPU variants: Upgraded to Ubuntu 24.04 (from 22.04)
• CUDA 12.8/13 variants: Ubuntu 24.04
• CUDA 12.4 variant: Remains on Ubuntu 22.04 (for compatibility)

📦 Package Updates

Core Scientific Stack

• NumPy: 2.3.4
• SciPy: 1.16.3
• Matplotlib: 3.10.7
• Astropy: 7.1.1
• Python: 3.12 (Ubuntu 24.04) / 3.11 (Ubuntu 22.04)

GPU Packages by CUDA Variant

CUDA 12.4 (Ubuntu 22.04):

• PyTorch: 2.3.1+cu121 (with cuDNN 8.9 compatibility)
• JAX: 0.4.26 (with cuDNN 8.9 compatibility)
• CuPy: 13.6.0 (cuda12x)
• CUDA: 12.4.0

CUDA 12.8 (Ubuntu 24.04):

• PyTorch: 2.9.0+cu128
• JAX: 0.8.0
• CuPy: 13.6.0 (cuda12x)
• CUDA: 12.8.1

CUDA 13 (Ubuntu 24.04):

• PyTorch: 2.9.0+cu130
• JAX: 0.8.0
• CuPy: 13.6.0 (cuda13x)
• CUDA: 13.0.1

JAX Ecosystem (CUDA 12.8/13)

• BlackJAX: 1.2.5
• NumPyro: 0.19.0
• PyMC: 5.26.1
• Flax: 0.12.0
• TensorBoard: 2.20.0

🏷️ Tagging

All images are tagged with version v0.2.0 and include OS information:

• v0.2.0-cpu-ubuntu24.04
• v0.2.0-cpu-singularity-ubuntu24.04
• v0.2.0-gpu-cu124-ubuntu22.04
• v0.2.0-gpu-cu124-singularity-ubuntu22.04
• v0.2.0-gpu-cu128-ubuntu24.04
• v0.2.0-gpu-cu128-singularity-ubuntu24.04
• v0.2.0-gpu-cu13-ubuntu24.04
• v0.2.0-gpu-cu13-singularity-ubuntu24.04

Moving aliases (cpu, gpu-cu124, gpu-cu128, gpu-cu13, etc.) have been updated to point to v0.2.0.

📥 Quick Start

# Pull CPU variant (multi-arch: amd64/arm64)
docker pull vhaasteren/anpta:cpu

# Pull GPU variants (amd64 only)
docker pull vhaasteren/anpta:gpu-cu124  # CUDA 12.4
docker pull vhaasteren/anpta:gpu-cu128  # CUDA 12.8
docker pull vhaasteren/anpta:gpu-cu13   # CUDA 13

🔧 Build Instructions

Build and push all variants:

docker login
./scripts/push_to_registry.sh dockerhub

📚 Documentation

• Updated documentation for all 8 variants
• See docs/PUBLISHING_DOCKERHUB.md for publishing workflow
• See docs/DOCKERHUB_README.md for usage instructions

🔗 Links

• Docker Hub: https://hub.docker.com/r/vhaasteren/anpta
• Documentation: See repository docs/ directory
• Issues: Report issues on GitHub

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Full Changelog: See commit history for detailed changes.

v0.1.0

Version 0.1.0, also on Dockerhub