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                                            dikeke

X11 error (xhost +SI:localuser:root allows the root user to access the running X server.)

> It just works.

后执行且低优先级的多个小job总是比先执行高优先级的大job先运行

Is there any progress?

后执行且低优先级的多个小job总是比先执行高优先级的大job先运行

> I have an idea to solve it. But if will waste computility if keeping the resource free and don't let the low-priority small requested jobs to run. > >...

Add usage in response like openai?

any progress on this issue?

scale down allreduct pytorch job won't complete and report error

假设集群可用cpu资源为4份。创建两个pod,占用2份cpu资源。创建torch-mnist job,设置min_node=2,node-unit=2,max_node=$NODE_NUM,NODE_NUM=4。每个node需要占用1份cpu资源。 3.1 保持资源状况直到训练结束（修改代码) job会有两个worker处于running状态，其他两个worker处于pending状态。两个worker组成rendezvous，并完成训练，状态转换成complete.其他两个pending worker获得资源，转换成running状态，继续训练，但会报错，训练始终无法完成

dikeke

X11 error (xhost +SI:localuser:root allows the root user to access the running X server.)

support aarch64

后执行且低优先级的多个小job总是比先执行高优先级的大job先运行

后执行且低优先级的多个小job总是比先执行高优先级的大job先运行

这个限流库两个大bug存在了半年之久，没人发现？

Add usage in response like openai?

scale down allreduct pytorch job won't complete and report error