Create/Plan Instance Type
Instance Type, is a resources allocation setting. According to the it, PrimeHub will try to allocate these resources for launching an instance for a JupyterHub or a Job if vacant resources are sufficient.
This quckstart shows how to crete an instance type and give an advice of planning them according to a real circumstance (CPUs/MEM/GPUs).
Advice of Plan
In a real circumstance, we have to manage/arrange resources of CPUs, Memory or even GPUs. For the sake of resources utilization, via instance types, we can plan our resources for different groups/projects according to different demands for computing resources. A good arrangement of instance types can not only utilize resources efficient, but also can prevent an instance from occupying massive resources.
Since PrimeHub cluster uses certain of resources for operating the cluster properly, we are not able to allocate all of resources for running instances. It is recommended to leave 10%-15% resources of CPU/MEM for the cluster itself.
Projects require various computing resources. We can start arranging/planning our instance types for different scales of resources allocations (such as small/medium/large), users can choose the appropriate scale of instance type for projects for the allocation of requested resources. We, of course, can create a specific instance type for a specific project as well.
If you are new to plan instance types, here is an advice.
Let's assume a circumstance of CPU 40 / MEM 512GB / GPU 4:
CPU-Only instance type
Scale | CPU | Mem | % of Total |
---|---|---|---|
Small | 4 | 128G | 10-25 |
Medium | 16 | 256G | 40-60 |
Large | 32 | 420G | 80+ |
GPU-Equipped instance type
Scale | CPU | Mem | GPU | % of Total |
---|---|---|---|---|
Small | 4 | 128G | 1 | 10-25 |
Medium | 16 | 256G | 2 | 40-60 |
Large | 32 | 420G | 4 | 80+ |
Let's Add Instance Types
According to our plan, let's create instance types for users, here we will create a GPU-equipped instance type of medium-scale.
Log in as an administrator and switch to Admin Portal.
Enter
Instance Types
management.Fill in
Name
with medium-with-gpu.Fill in
CPU Limit
with 16 and fill inMemory Limit
with 256GB.Fill in
GPU Limit
with 2.(Optional)
Overcommitting
, if required, enabled it and fill inCPU Request
with 14 andMemory Request
with 200GB. More detail [Overcommitting].Click
edit groups
and select groups which can have this instance type.(Optional)
Tolerations
if required: [Reference](Optional)
NodeSelector
if required: [Reference]Click
Confirm
to save it.
Next
We have created the instance type, medium-with-gpu, which requests medium-scale resources allocation and assigned it to groups. Users who belong to these groups are able to select it for launching instances. Next, let's add images as working environments for instances.