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Jolien-S merged 5 commits into from
Jul 11, 2025
Merged

clarify availability of GPUs in community partition #470

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435ee66
update on GPU availability #439
peer35 Jun 26, 2025
6d22eed
community partition
peer35 Jun 26, 2025
3b99e70
fix negative
peer35 Jun 26, 2025
7601a1b
Merge branch 'main' into adagpu439
peer35 Jun 26, 2025
f00829a
Update topics/ada.qmd
Jolien-S Jul 11, 2025
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4 changes: 2 additions & 2 deletions topics/ada.qmd
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Expand Up @@ -11,7 +11,7 @@ ADA is a high performance compute (HPC) cluster for research at the Vrije Univer

ADA is a heterogenious cluster composed of partitions and servers financed by various VU research departments and the VU IT department. The cluster is particularly useful for executing multi-node computations that are not possible on the general VU compute servers but do not require the scale of the National Supercomputer, Snellius.

ADA users are granted access to a set of compute partitions based on the resources owned by their research department. Users not affiliated with a research department that owns cluster hardware can get access to the general (IT) partition.
ADA users are granted access to a set of compute partitions based on the resources owned by their research department. Users not affiliated with a research department that owns cluster hardware can get access to the community partition.

A large collection of tools, compilers and libraries is available for your analysis, and your data on [SciStor](../topics/SciStor.qmd) are directly accessible from ADA.

Expand All @@ -28,7 +28,7 @@ Be aware that it is generally not possible to run graphical desktop applications
CLI and scripting skills are very useful to have for every researcher, but if you feel you do not have the time to learn these skills there might be other options available such as [the VU Compute Hub](https://hub.compute.vu.nl) or [SURF Research Cloud](../topics/researchcloud.qmd) where you can run some graphical tools.

### GPUs in ADA
Some workloads, such as Machine Learning, require a GPU. At the moment the compute nodes in the ADA general (IT) partition do not have GPUs. If your department also has no dedicated compute nodes with GPUs, you can apply for access to the national HPC infrastructure [Snellius](../topics/snellius.qmd) or consider [buying ADA compute nodes](#buying-dedicated-compute-nodes) with GPU nodes for your department.
Some workloads, such as Machine Learning, require a GPU. At the moment only some of the compute nodes in the ADA community partition have GPUs, the availability is not sufficient for everyone at any given time. If your workload requires more extensive use of GPUs and your department has no dedicated compute nodes with GPUs, you can apply for access to the national HPC infrastructure [Snellius](../topics/snellius.qmd) or consider [buying ADA compute nodes](#buying-dedicated-compute-nodes) with GPUs for your department.

## How to request access

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