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Running on Zero
| # RANGE CUDA preview | |
| This preview publishes the **retained Phase60 CUDA pipeline**, previously installed | |
| and measured in Phase61. Its CUDA binary and private exact CPU fallback are | |
| byte-identical to that installation. The current integration changes package imports | |
| and connects the pipeline to the maintained RANGE API. | |
| **Public Python package release is coming soon.** These are preview wheels, not a | |
| PyPI release. The hosted app runs on CPU; downloading its CUDA preview gives you a | |
| separate local GPU execution path. | |
| ## Install the preview | |
| Use **64-bit Windows, CPython 3.10, and an NVIDIA sm75 GPU** with a compatible CUDA | |
| 12 driver/runtime. The original qualification used an RTX 2070 Max-Q. Other GPU | |
| architectures and Linux CUDA execution are not supported by this preview. CPU-only | |
| users can install the CPU wheel without the CUDA companion. | |
| Download both matching files from the Space's `downloads` folder: | |
| - [RANGE CPU wheel](https://huggingface.co/spaces/Brianferrell787/range/resolve/main/downloads/range_curate-0.1.0a3-cp310-cp310-win_amd64.whl) | |
| - [RANGE CUDA companion](https://huggingface.co/spaces/Brianferrell787/range/resolve/main/downloads/range_curate_cuda-0.1.0a3-cp310-cp310-win_amd64.whl) | |
| From the folder containing both downloads, create a Python 3.10 environment and | |
| install both files together: | |
| ```powershell | |
| py -3.10 -m venv .venv | |
| .\.venv\Scripts\python.exe -m pip install .\range_curate-0.1.0a3-cp310-cp310-win_amd64.whl .\range_curate_cuda-0.1.0a3-cp310-cp310-win_amd64.whl | |
| ``` | |
| Pip installs the companion's pinned CuPy, NumPy, PyArrow and CUDA-pathfinder | |
| dependencies. No RANGE Rust or CUDA compilation is needed to install these wheels. | |
| A compatible NVIDIA driver/runtime is still required. The port was checked with | |
| existing installed dependencies; a fresh dependency download on another machine | |
| has not been qualified. | |
| ## Run bulk Arrow screening | |
| ```python | |
| from datetime import datetime, timezone | |
| import pyarrow as pa | |
| from range_curate.examples.general_economy import RelevanceEngine | |
| engine = RelevanceEngine(backend="cuda", workers=10) | |
| data = pa.table({ | |
| "text": ["The Federal Reserve cut interest rates."], | |
| "timestamp": pa.array( | |
| [datetime(2025, 1, 15, tzinfo=timezone.utc)], | |
| type=pa.timestamp("us", tz="UTC"), | |
| ), | |
| }) | |
| facts = engine.screen_arrow(data).to_pyarrow() | |
| ``` | |
| CUDA applies to **bulk `screen_arrow`**. Rich predictions, explanations, list | |
| screening, and the domain-neutral `CurationEngine` continue to run on CPU. A tiny | |
| example demonstrates the API, not GPU throughput. The CUDA input is a materialized | |
| Arrow Table or RecordBatch with non-null text and timezone-aware timestamps. | |
| You can pass a supported custom `Taxonomy` using `taxonomy=...`. The pipeline uses | |
| exact CPU fallback for unsupported rules and rows that exceed its GPU bounds. | |
| Missing or incompatible CUDA raises a clear error; it does not silently substitute | |
| a CPU run for a failed GPU runtime. Choose `backend="cpu"` explicitly for CPU use. | |
| ## What the speed record means | |
| Phase60 measured **1,833,059 articles/s** and the Phase61 installation measured | |
| **1,809,133 articles/s** on their recorded General Economy workload. This preview | |
| contains that retained pipeline. Six finite installed correctness checks passed | |
| for the current API port. **No performance experiment was rerun**, at the | |
| maintainer's request; this is not a new timing claim for the renamed wheel. | |
| The kernel SHA-256 is | |
| `dd943d9adac702e41c2bb0a2b58f78698498edd8a3dfab16cf9d224c8c6a83fa`. | |
| The private CPU fallback SHA-256 is | |
| `8b1dddd69ccc13380cced1f2df4977f2ecb750805c9d127b0c8046fef812563f`. | |
| See [the integration record](INTEGRATION_RECORD.json), [source provenance](provenance.json), | |
| and [benchmark conditions](https://huggingface.co/spaces/Brianferrell787/range/blob/main/BENCHMARKS.md). The source tree includes the retained | |
| orchestration and CUDA kernels. `build_wheel.py` assembles the companion from the | |
| hash-bound Phase61 reference wheel and the matching current CPU wheel; it preserves | |
| third-party notices and records all packaged file hashes. | |