Hi guys. I am facing a problem here.
I have a computation task that roughly utilizes 70% of single GPU computation power but with little consumption of the memory. Ideally, I want to put two tasks on a single to fully utilize the resources. In my code, I set
num_gpus=0.5 for each task.
When I run 8 tasks on a server with 4 GPUs, everything works as expected. However, if I only run 4 tasks, these tasks will only be scheduled on 2 GPUs, leaving the other two unused. I understand ray is trying to save the card for other tasks that may require a whole GPU. But it is not efficient in my case. Is there any hack that I can use to make the 4 tasks scheduled evenly on 4 cards?