1. welcome
  2. Hello World
  3. Open Source
  4. 1. vllm
  5. 2. pytorch
    ❱
    1. 2.1. torchrun
    2. 2.2. tensor
    3. 2.3. autograd
    4. 2.4. operator
    5. 2.5. profiler
    6. 2.6. hook
    7. 2.7. elastic
    8. 2.8. patch
    9. 2.9. misc
  6. 3. paddlepaddle
    ❱
    1. 3.1. ps
    2. 3.2. framework
    3. 3.3. cinn
    4. 3.4. dataloader
  7. 4. horovod
    ❱
    1. 4.1. run
    2. 4.2. workflow
    3. 4.3. object
    4. 4.4. develop
    5. 4.5. pytorch
    6. 4.6. tensorflow
    7. 4.7. elastic
  8. 5. ray
    ❱
    1. 5.1. overview
    2. 5.2. gcs
    3. 5.3. raylet
    4. 5.4. api
    5. 5.5. survey
  9. 6. llama
  10. 7. nccl
  11. 8. megatron
  12. 9. deepspeed
  13. Survey
  14. 10. survey
    ❱
    1. 10.1. pollux
    2. 10.2. adasum
    3. 10.3. adaptation_learning
    4. 10.4. gradient_descent
    5. 10.5. auto_parallel
    6. 10.6. scheduling
    7. 10.7. gradient_compression
      ❱
      1. 10.7.1. dgc
      2. 10.7.2. csc
    8. 10.8. flash attention
    9. 10.9. LoRA
  15. 11. models
    ❱
    1. 11.1. llm
    2. 11.2. falcon
    3. 11.3. llama
    4. 11.4. peft
    5. 11.5. transformer
    6. 11.6. models
  16. Programming
  17. 12. python
    ❱
    1. 12.1. concurrent execution
    2. 12.2. multiprocessing
    3. 12.3. decorator
  18. 13. golang
    ❱
    1. 13.1. golang error
  19. 14. cplusplus
    ❱
    1. 14.1. enable_shared_from_this
  20. Mathematics
  21. 15. mathematics
    ❱
    1. 15.1. basic
    2. 15.2. entropy
    3. 15.3. newton
    4. 15.4. regression
    5. 15.5. conjugate descent
    6. 15.6. gradient descent
    7. 15.7. pca
    8. 15.8. support vector
    9. 15.9. differentiation
    10. 15.10. fourier
    11. 15.11. kmeans
  22. 16. wavelets
    ❱
    1. 16.1. plan
    2. 16.2. preliminary
    3. 16.3. haar wavelet
    4. 16.4. fourier analysis
    5. 16.5. uncertainty principle
    6. 16.6. multiresolution
  23. Learning Deep
  24. 17. kubernetes
    ❱
    1. 17.1. concepts
    2. 17.2. scheduler
    3. 17.3. operator
    4. 17.4. device plugin
    5. 17.5. docker
    6. 17.6. install
    7. 17.7. api-service
    8. 17.8. controller
  25. 18. cuda
  26. 19. todo
    ❱
    1. 19.1. gloo
    2. 19.2. mpi
    3. 19.3. jax
    4. 19.4. tvm
    5. 19.5. llm
  27. 20. notes
    ❱
    1. 20.1. influence and persuasion
    2. 20.2. freynman technique
    3. 20.3. wavelet signal processing
  28. 21. tips
    ❱
    1. 21.1. ip_local_port_range
  29. 22. infrastructure
    ❱
    1. 22.1. pki
    2. 22.2. linux cache
  30. 23. projects
    ❱
    1. 23.1. copilot
    2. 23.2. library
    3. 23.3. RAG
  31. 24. chronicles
    ❱
    1. 24.1. feb 2024

Aller au boulot

scheduler

Summary and Examples

比较简单的 demo,体现基本框架

GitHub - Huang-Wei/sample-scheduler-extender: a sample to showcase how to create a k8s scheduler extender

稍微复杂一些,完整实现,extender 部署

GitHub - everpeace/k8s-scheduler-extender-example: An example of kubernetes scheduler extender

aliyun gpu,部署替换 kube-scheduler

GitHub - AliyunContainerService/gpushare-scheduler-extender: GPU Sharing Scheduler for Kubernetes Cluster

基于 kubernetes framework

GitHub - everpeace/kube-throttler: throttling your pods in kubernetes cluster.

Reference

  • design-proposals-archive/scheduler_extender.md at main · kubernetes/design-proposals-archive · GitHub

  • Scheduling Framework | Kubernetes

  • enhancements/README.md at master · kubernetes/enhancements · GitHub