Clusters with Gpus under Linux and Windows HPC
Clusters with Gpus under Linux and Windows HPC Clusters with Gpus under Linux and Windows HPC
After Deployment… • Custom software can be added with postdeployment steps, configurable in the UI and persisted in XML – It helps to have an unattended command-line way to install the software, to avoid prompting user – Examples: • Windows Debugger • CUDA Toolkit, CUDA SDK • Steps to control how and when OS patches are deployed are built into the management tools
CUDA Toolkit • To automate the toolkit deployment – Generate a setup.iss file: cudatoolkit -r This will generate the setup.iss in C:\Windows – Use this file for unattended installation on all the nodes: cudatoolkit -s -f1”fullpathto\file.iss” • Same steps for the CUDA SDK.
- Page 1 and 2: Clusters with GPUs under Linux and
- Page 3 and 4: HPC Clusters • Clusters are very
- Page 5 and 6: CUDA software requirements • Driv
- Page 7 and 8: Linux for GPU clusters
- Page 9 and 10: System management for Tesla S1070 n
- Page 11 and 12: Windows HPC for GPU clusters Curren
- Page 13 and 14: Deployment Means… 1. Getting the
- Page 15 and 16: Network Drivers Management Overall
- Page 17: Images, drivers, and all that • A
- Page 21 and 22: Leveraging the GPU • A special en
- Page 23: Thank You! • www.nvidia.com/cuda
After Deployment…<br />
• Custom software can be added <strong>with</strong> postdeployment<br />
steps, configurable in the UI <strong>and</strong><br />
persisted in XML<br />
– It helps to have an unattended comm<strong>and</strong>-line way to<br />
install the software, to avoid prompting user<br />
– Examples:<br />
• <strong>Windows</strong> Debugger<br />
• CUDA Toolkit, CUDA SDK<br />
• Steps to control how <strong>and</strong> when OS patches are<br />
deployed are built into the management tools
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