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Free GPU smoke/evaluation

A free GPU can test a small PointNeXt release path, but not every benchmark.

Good free-GPU targets

  • Google Colab Free, usually T4/K80/P100 depending on availability.
  • Kaggle Notebook GPU, often T4/P100.
  • Similar free notebook environments with one CUDA GPU and a working compiler.

These are suitable for:

  • pip install pointnext_official import checks.
  • source checkout with CUDA op build.
  • ModelNet40 dataset auto-download.
  • ModelNet40 PointNeXt-S C=64 checkpoint download and SHA-256 verification.
  • a single ModelNet40 test/smoke run.

Not realistic on free GPU

  • full S3DIS or ScanNet training
  • multi-GPU training
  • exhaustive segmentation benchmarking
  • large ablation sweeps

Colab notebook

Use:

notebooks/colab_free_modelnet40_smoke_eval.ipynb

The notebook performs:

  1. GPU check.
  2. clone with submodules.
  3. install source dependencies.
  4. build PointNeXt/OpenPoints CUDA ops.
  5. download the ModelNet40 PointNeXt-S C=64 checkpoint from Hugging Face Hub.
  6. verify SHA-256 when metadata/checksums.sha256 is available.
  7. run the ModelNet40 evaluation command.

Expected released checkpoint result: about OA 94.0 / mAcc 91.1. For a quick smoke test, successful import, CUDA op build, checkpoint download/hash verification, dataset load, and a completed evaluation loop are the pass criteria.