Demystify RAM Usage in Multi-Process Data Loaders
Read OriginalThis technical article analyzes a common problem in PyTorch where using multi-process data loaders can replicate a dataset's RAM usage up to 40 times. It explains why this happens with in-memory metadata, provides tools to accurately measure RAM usage (USS, PSS), and offers solutions to enable memory sharing across processes to drastically reduce memory footprint. The concepts apply to any Python multiprocessing on Linux.
Demystify RAM Usage in Multi-Process Data Loaders
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