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  "text": "TRANSIT (TRANsparent Scale-In for multi-node Training) is a runtime that makes unified virtual memory practical for large-scale LLM training, enabling models to train on up to 50% fewer GPUs without requiring modification to existing PyTorch training code.\n\nHyungyo Kim, Ph.D. Candidate in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign will present on TRANSIT as a poster at PyTorch Conference North America with Apoorve Mohan from IBM Research.\n\nLearn how to train more with less at PyTorch Conference North America: https://t.co/jBApW8nESi",
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