Extended Data Fig. 10: Memory and run-time benchmarking for training CellLENS on datasets of different sizes. | Nature Immunology

Extended Data Fig. 10: Memory and run-time benchmarking for training CellLENS on datasets of different sizes.

From: CellLENS enables cross-domain information fusion for enhanced cell population delineation in single-cell spatial omics data

Extended Data Fig. 10

We ran CellLENS on increasing numbers of cells: ~10k, ~50k, ~150k, ~500k, ~1.5 mil, and recorded the memory and run-time statistics. The benchmarking was performed on an NVIDIA A5000 GPU with an SSD disk (PCIe 4.0) for I/O. Left panel: GPU memory usage during CNN and GNN training stages of CellLENS, across variable cell numbers. Middle panel: Run-times of CellLENS CNN training stage. Recorded run-time for both default LENS-CNN or LENS-CNN with a ViT architecture. Right panel: Run-time of CellLENS GNN training stage.

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