This is an automated email from the ASF dual-hosted git repository.
hcr pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/mahout.git
The following commit(s) were added to refs/heads/main by this push:
new 02e075632 [bug] add back getting started (#1019)
02e075632 is described below
commit 02e0756323b6aceee5ae4df600eda209a4b8d9b9
Author: Ryan Huang <[email protected]>
AuthorDate: Fri Feb 6 14:33:36 2026 +0800
[bug] add back getting started (#1019)
---
docs/qdp/getting-started.md | 80 ++++++++++++++++++++++++++++++++++++++++++---
1 file changed, 76 insertions(+), 4 deletions(-)
diff --git a/docs/qdp/getting-started.md b/docs/qdp/getting-started.md
index 8fdf88656..33625aab0 100644
--- a/docs/qdp/getting-started.md
+++ b/docs/qdp/getting-started.md
@@ -2,8 +2,80 @@
title: Getting Started with QDP
---
-# Getting Started
+# Getting Started with QDP
-:::info Coming Soon
-This documentation is under development. Check back soon!
-:::
+QDP (Quantum Data Plane) is a GPU-accelerated library for encoding classical
data into quantum states.
+
+## Prerequisites
+
+- Linux with NVIDIA GPU
+- CUDA toolkit installed (`nvcc --version` to verify)
+- Python 3.10+
+
+## Installation
+
+```bash
+pip install qumat[qdp]
+```
+
+For development (from source):
+
+```bash
+git clone https://github.com/apache/mahout.git
+cd mahout/qdp/qdp-python
+uv venv -p python3.10 && source .venv/bin/activate
+uv sync --group dev && uv run maturin develop
+```
+
+## Quick Start
+
+```python
+import torch
+from qumat.qdp import QdpEngine
+
+engine = QdpEngine(0) # GPU device 0
+data = [0.5, 0.5, 0.5, 0.5]
+qtensor = engine.encode(data, num_qubits=2, encoding_method="amplitude")
+
+# Convert to PyTorch (zero-copy)
+tensor = torch.from_dlpack(qtensor) # Note: can only be consumed once
+```
+
+## Encoding Methods
+
+| Method | Constraint | Example |
+|--------|-----------|---------|
+| `amplitude` | data length ≤ 2^num_qubits | `encode([0.5, 0.5, 0.5, 0.5],
num_qubits=2, encoding_method="amplitude")` |
+| `angle` | data length = num_qubits | `encode([0.1, 0.2, 0.3, 0.4],
num_qubits=4, encoding_method="angle")` |
+| `basis` | data length = num_qubits | `encode([1, 0, 1, 1], num_qubits=4,
encoding_method="basis")` |
+
+## File Inputs
+
+```python
+engine.encode("data.parquet", num_qubits=10, encoding_method="amplitude") #
also: .arrow, .npy, .pt, .pb
+```
+
+## Tips
+
+- Use `precision="float64"` for higher precision: `QdpEngine(0,
precision="float64")`
+- NumPy inputs must be `float64` dtype
+- Streaming only works with Parquet files
+
+## Troubleshooting
+
+| Problem | Solution |
+|---------|----------|
+| Import fails | Activate venv: `source .venv/bin/activate` |
+| CUDA errors | Run `cargo clean` in `qdp/` and rebuild |
+| Out of memory | Reduce `num_qubits` or use `precision="float32"` |
+
+## Next Steps
+
+- [Concepts](../concepts/) - Learn about quantum encoding concepts
+- [API Reference](../api/) - Detailed API documentation
+- [Examples](../examples/) - More usage examples
+
+## Help
+
+- Mailing List: [email protected]
+- [GitHub Issues](https://github.com/apache/mahout/issues)
