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The document analyzes overheads from end-to-end (E2E) execution traces of various models on V100 GPUs, revealing that T1 overheads are consistent across different models and batch sizes, averaging around 8 µs. The E2E training performance model for DLRM shows a prediction error of 7.96% for E2E time, indicating the effectiveness of including overhead modeling in performance predictions. The findings suggest that as batch size increases, the gap between E2E and kernel-only predictions narrows due to improved

Author

heistpranking

Language

EN