vkdispatch-core 0.0.34

A Python module for orchestrating and dispatching large computations across multi-GPU systems using Vulkan.

Getting Started

Welcome to vkdispatch! This guide will help you install the library and run your first GPU-accelerated code.

[WARNING: The documentation is still under heavy development, and has many missing sections]

Note: vkdispatch requires a Vulkan-compatible GPU and drivers installed on your system. Please ensure your system meets these requirements before proceeding.

Installation

The default installation method for vkdispatch is through PyPI (pip):

# Install the package
pip install vkdispatch

On mainstream platforms — Windows (x86_64), macOS (x86_64 and Apple Silicon/arm64), and Linux (x86_64) — pip will download a prebuilt wheel (built with cibuildwheel on GitHub Actions and tagged as manylinux where applicable), so no compiler is needed.

On less common platforms (e.g., non-Apple ARM or other niche architectures), pip may fall back to a source build, which takes a few minutes. See Building From Source for toolchain requirements and developer-oriented instructions.

Tip: If you see output like Building wheel for vkdispatch (pyproject.toml), you’re compiling from source.

Verifying Your Installation

To ensure vkdispatch is installed correctly and can detect your GPU, run:

# Quick device listing
vdlist

# If the above command is unavailable, try:
python3 -m vkdispatch

If the installation was successful, you should see output listing your GPU(s), for example:

Device 0: Apple M2 Pro
    Vulkan Version: 1.2.283
    Device Type: Integrated GPU

    Features:
        Float32 Atomic Add: True

    Properties:
        64-bit Float Support: False
        16-bit Float Support: True
        64-bit Int Support: True
        16-bit Int Support: True
        Max Push Constant Size: 4096 bytes
        Subgroup Size: 32
        Max Compute Shared Memory Size: 32768

    Queues:
        0 (count=1, flags=0x7): Graphics | Compute
        1 (count=1, flags=0x7): Graphics | Compute
        2 (count=1, flags=0x7): Graphics | Compute
        3 (count=1, flags=0x7): Graphics | Compute

Next Steps

• Tutorials — our curated guide to common workflows and examples
• Full Python API Reference — comprehensive reference for Python-facing components

Happy GPU programming!