Deep Dive - CRI- RM Based CPU and NUMA Affinity to Achieve AI Task Acceleration

Deep Dive - CRI- RM Based CPU and NUMA Affinity to Achieve AI Task Acceleration

CNCF [Cloud Native Computing Foundation] via YouTube Direct link

Run Al training tasks on the CPU

14 of 20

14 of 20

Run Al training tasks on the CPU

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Deep Dive - CRI- RM Based CPU and NUMA Affinity to Achieve AI Task Acceleration

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Intro
  2. 2 Content
  3. 3 CRI-RM architecture
  4. 4 Noisy neighbors
  5. 5 Latency critical workloaus
  6. 6 CPU clock speed throtung
  7. 7 Available resource and control
  8. 8 Topology aware policy
  9. 9 Static-pools policy
  10. 10 CRI-RM node agent
  11. 11 CRI-RM webhook
  12. 12 Topology-aware resource alignment
  13. 13 Some problems In Al training cluster (Kubernetes* + Docker*)
  14. 14 Run Al training tasks on the CPU
  15. 15 CPU management in Kubernetes
  16. 16 Kubernetes* integrated CRI-RM
  17. 17 Test environment
  18. 18 Test casel: restnet50+imagenet
  19. 19 Test case2: CNN+minst
  20. 20 Conclusion

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.