Make simulate_pixels.py more robust against huge tracks datasets #102
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…t, add segment_id to tracks dataset
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I see the same improved performance. |
peter-madigan
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fix/improve-stability-for-large-tracks-datasets
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For the 2x2 file that @krwood provided me, I no longer encounter memory overruns on a single CORI 16GB Tesla V100 gpu with a
tracksdataset containing 20M entries.The tracks dataset is still loaded up front which takes approx ~30s. The dataset is then filtered on the CPU (~20s), which could probably be sped up by copying the xyz data to the GPU. The subsequent simulation then only takes about another 20s.