~/talk

Accelerating Model Training on Ascend Chips: An Industrial System for Profiling...

on YouTube 13m
Talkat USENIX ATC '25 · 2025-07-07..07-09· [machine-learning]

speakers

name:Yuhang Zhou
links:none on file
name:Zibo Wang
links:none on file
name:Zhibin Wang
links:none on file
name:Ruyi Zhang
links:none on file
name:Chen Tian
links:none on file
name:Xiaoliang Wang
links:none on file
name:Wanchun Dou
links:none on file
name:Guihai Chen
links:none on file
name:Bingqiang Wang
links:none on file
name:Yonghong Tian
links:none on file
name:Yan Zhang
links:none on file
name:Hui Wang
links:none on file
name:Fuchun Wei
links:none on file
name:Boquan Sun
links:none on file
name:Jingyi Zhang
links:none on file
name:Bin She
links:none on file
name:Teng Su
links:none on file
name:Yifan Yao
links:none on file
name:Chunsheng Li
links:none on file
name:Ziyang Zhang
links:none on file
name:Yaoyuan Wang
links:none on file
name:Bin Zhou
links:none on file
name:Guyue Liu
links:none on file

resources

video:https://youtu.be/6E0fgv8oriU
slides:none on file

summary

Hermes is an industrial system that combines cost-to-find profiling (lightweight monitor that triggers fine-grained traces) with a hierarchical inter- and intra-operator bottleneck analysis and an MST advisor that maps observed costs to fixes from 135 real-world cases. It reports low runtime overhead, fixes CPU scheduling and AI‑CPU underutilization, and catches issues like port flapping and Python GC. Real experiments show speedups such as PanGu-α 3.05×, MobileNetV1 1.91×, MoE 1.19× and per-case gains up to 5.34×.

AI-written summary · about

chapters (15)

  1. 0:00Introduction
  2. 0:41Model training complexity
  3. 2:06Profiling tool limitations
  4. 2:51Ascend chips insights
  5. 4:16Bottleneck analysis framework
  6. 5:39Hermas profiling mechanism
  7. 6:22Interoperator parallelism
  8. 7:05IO bottleneck detection
  9. 7:28CPU bottleneck causes
  10. 7:50Roofline model categorization
  11. 8:12Communication bottleneck analysis
  12. 8:33MST advisor tool
  13. 8:53Five lessons from cases
  14. 9:57Case studies speedups
  15. 11:49Conclusion

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