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Hi All, Is There A Way To Schedule The Tasks From The Queue Onto The Gpu Instances Based On Factors Such As Gpu Utilisation, Number Of Cpu Cores Present, Free Memory Or Custom Parameters Such As Priority Of The Task, Estimated Time Etc?


Hi CharmingPuppy6
Basically yes there is.
The way clearml is designed, is to have queues abstract different types pf resources. for example a queue for single gpu jobs (let's nam "single_gpu") and a queue for dual gpu jobs (let's name it "single_gpu").
Then you spin agents on machines and have the agents pull jobs from specific queues based on the hardware they have. For example we can have a 4 GPU machine with 3 agents, one agent connect to 2xGPUs and pulling Tasks from the "dual_gpu" queue, and then two more agents each one connect with a single gpu, pulling Tasks from "single_gpu" queue. The same idea also scales if you connect it to a Kubernetes cluster isntead of bare-metal / cloud.
Does that answer the question ?

  
  
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