vultorch 0.3.5

Real-time Torch visualization window with Vulkan zero-copy

🔥 Vultorch

Real-time Torch Visualization Window · Vulkan Zero-Copy

Visualize CUDA tensors at GPU speed — zero CPU readback, zero staging buffers.

🇨🇳 中文 · 🌐 Website

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Overview

Vultorch displays CUDA tensors in a native window — data never leaves the GPU. show() performs a fast GPU-GPU copy; create_tensor() eliminates even that via Vulkan shared memory.

vultorch.show(tensor)           # GPU-only, no CPU readback
tensor = vultorch.create_tensor(...)  # true zero-copy, no memcpy at all

Key Features

• GPU-only display — vultorch.show(tensor) does a fast GPU-GPU copy to Vulkan, no CPU readback ever
• True zero-copy — vultorch.create_tensor() returns a torch.Tensor backed by Vulkan shared memory — zero memcpy
• Declarative API — View → Panel → Canvas with auto layout and per-frame callback support
• Built-in ImGui — Sliders, buttons, color pickers, plots, docking layout — all from Python
• 3D scene view — Map textures onto lit 3D planes with orbit camera, MSAA, Blinn-Phong shading
• Docking windows — Drag-and-drop window arrangement (ImGui docking branch)

Quick Start

pip install vultorch

import torch, vultorch

# Your neural texture output (or any CUDA tensor)
texture = torch.rand(512, 512, 4, device="cuda")

view = vultorch.View("Neural Texture Viewer", 800, 600)
panel = view.panel("Output")
panel.canvas("main").bind(texture)
view.run()

True Zero-Copy

# Shared GPU memory — writes are instantly visible on screen
tensor = vultorch.create_tensor(512, 512, channels=4)
tensor[:] = model(input)   # write directly, no copy needed

3D Scene

scene = vultorch.SceneView("3D", 800, 600, msaa=4)
scene.set_tensor(texture)
scene.render()  # orbit camera, Blinn-Phong lighting

Examples

Example	Description
01_hello_tensor.py	Minimal tensor display
02_imgui_controls.py	Multi-panel layout with docking
03_training_test.py	Tiny network live training (GT vs prediction + bottom info panel)

python examples/01_hello_tensor.py

Building from Source

Prerequisites

Component	Required	Notes
GPU	✅	Any Vulkan-capable GPU (NVIDIA, AMD, Intel)
Vulkan	Runtime	Ships with your GPU driver — no separate install needed
Vulkan SDK	Build only	lunarg.com/vulkan-sdk — only for building from source
CUDA Toolkit	Optional	For show() and create_tensor()
Python 3.8+	✅
CMake 3.25+	Build only	+ Ninja

Clone & Build

git clone --recursive https://github.com/ChenlizheMe/Vultorch.git
cd Vultorch

One command — configure, compile, and produce a wheel in dist/:

# Windows
build.bat

# Linux
./build.sh

The wheel appears in dist/. Install it:

pip install dist/vultorch-*.whl

The build script auto-detects the active Python environment, so the wheel matches whichever python is on your PATH (conda, venv, system, etc.).

Architecture

vultorch/
├── src/                    # C++ core
│   ├── engine.cpp/h        # Vulkan + SDL3 + ImGui engine
│   ├── tensor_texture.*    # CUDA ↔ Vulkan zero-copy interop
│   ├── scene_renderer.*    # Offscreen 3D renderer (MSAA, Blinn-Phong)
│   ├── bindings.cpp        # pybind11 Python bindings
│   └── shaders/            # GLSL shaders → SPIR-V
├── vultorch/               # Python package
│   └── __init__.py         # High-level API (Window, show, SceneView)
├── external/               # Git submodules
│   ├── pybind11/           # C++ ↔ Python binding
│   ├── SDL/                # Window / input (SDL3)
│   └── imgui/              # Dear ImGui (docking branch)
├── examples/               # Ready-to-run demos
├── tools/                  # Build utilities
└── docs/                   # GitHub Pages website

License

MIT

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Examples · Website · 中文文档