I'm writing to you to ask for advice or a hint to the right direction.
In our department, more and more researchers ask us (IT administrators)
to assemble (or to buy) GPGPU powered workstations to do parallel computing.
As I already manage a small CPU cluster (resources managed using OGE),
with my boss we talked about building a new GPU cluster. The problem is
that I have no experience at all with GPU clusters.
Apart from the already running GPU workstations, we already have some
new HW that looks promising to me as a starting point for temporary
building and testing a GPU cluster.
- 1x Dell PowerEdge R720
- 1x Dell PowerEdge C410x
- 1x NVIDIA M2090 PCIe x16
- 1x NVIDIA iPASS Cable Kit
I'd be grateful if you could kindly give me some advice and/or hint to
the right direction.
In particular I'm interested on your opinion on:
1) is the above HW suitable for a small (2 to 4/6 GPUs) GPU cluster?
2) is OGE suitable (or what should we use?) as a queuing and resource
management system? We would like the cluster to be usable by many users
at once in a way that no user has to worry about resources, just like we
do on the CPU cluster with OGE.
3) What distribution of linux would be more appropriate?
4) necessary stack of sw? (cuda, OGE, torque, hadoop?, other?)
Any hint will be greatly appreciated.
Thank you very much for all your valuable insight!
The answer to Question 2 is Yes. Grid Engine is suitable as a resource manager for your GPU cluster. Check the Univa website for more info about Grid Engine.
As to the remaining questions, you may have to ask them in other forums which are Grid Engine related.