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Understand GPU management

INFO

Only Olares admins can change GPU modes. This helps avoid conflicts and keeps GPU performance predictable for everyone.

Olares lets you manage how apps use available GPUs for workloads such as AI, image and video generation, transcoding, and gaming.

In this guide, you will learn:

  • How GPU allocation works in Olares.
  • How app state affects available GPU actions.
  • How GPU modes differ and when to use each one.

How GPU allocation works

In Olares, giving an app access to GPU resources is called binding. Unbinding removes that access so the GPU can be released or reassigned.

Whether you can bind or unbind an app depends mainly on whether the app is running or stopped.

App stateBind (Give access)Unbind (Remove access)
RunningSupportedNot supported. You need to stop the app first. 1, 2
StoppedNot supported. You need to resume
the app first.
Supported
  1. Stopping an app pauses its workload, but it does not automatically remove its GPU allocation. To fully release the GPU or VRAM for other workloads, you must explicitly unbind the app after stopping it.
  2. If an app is allocated to multiple GPUs on the same node, you can unbind it from one GPU while it continues running on the others.

You can check whether an app is running or stopped in either of these places:

  • Market > My Olares: The current status is displayed on the app's card.
  • Settings > Applications: The current status is shown in the app list.
  • Launchpad: A stopped app is marked with an orange dot next to its name.

GPU modes and when to use them

Olares supports three GPU modes. Each mode determines how GPU resources are shared and what happens to running apps after you switch modes.

DGX Spark support

On DGX Spark, you can use Memory slicing and App exclusive to manage GPU resources.

GPU modeHow resources are
shared
After switching to this modeBest for
Time slicing (Default)Multiple apps share
the same GPU over
time.
Running apps that require a GPU are automatically assigned to share the GPU.Running several GPU-dependent apps at the same time.
Memory slicingMultiple apps share
the GPU, with fixed
VRAM allocations
for each app.
Running apps that require a GPU are automatically added and assigned the minimum VRAM required to run.Running multiple GPU-dependent apps while strictly controlling VRAM usage.
App exclusiveOne app gets full,
uninterrupted access
to the GPU.
One running app that requires a GPU is automatically selected and given exclusive access.Heavy workloads that need maximum performance, such as large models, rendering, or high-end gaming.

App interruption notice

Changing a GPU's mode reallocates hardware resources. Depending on the mode you choose, apps that are currently using the GPU may be paused automatically.

After switching modes, check the state of your apps and manually resume them if necessary.

Next steps