Difference between revisions of "Add resources (machines) to the pool"
From Supercomputación y Cálculo Científico UIS
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5. Add the resources with the following command: | 5. Add the resources with the following command: | ||
{{Command|<nowiki>source GPUresources.cmd</nowiki>}} | {{Command|<nowiki>source GPUresources.cmd</nowiki>}} | ||
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Latest revision as of 19:24, 9 April 2015

Add resources (machines) to the pool
Add the resources (new nodes) to OAR
1. Edit a file /tmp/nodos with the names of the new nodes (one per line)
File: /tmp/nodos
... guane12 guane17 . . ...
2. Then run the following command
oar_resources_init /tmp/nodos
3. Now run
source /tmp/oar_resources_init.cmd
4. Add GPU resources from nodes. Edit a file (GPUresources.cmd) with the following lines:
File: GPUresources.cmd
... oarnodesetting --sql "core=169" -p gpu=YES -p gpunum=57 -p gputype=M2075 oarnodesetting --sql "core=170" -p gpu=YES -p gpunum=57 -p gputype=M2075 oarnodesetting --sql "core=171" -p gpu=YES -p gpunum=57 -p gputype=M2075 . . ...
NOTE:
Each new core must correspond with the new GPU. In guane, for instance, where each node has 24 cores and 8 GPU, each GPU has been assigned to 3 cores. The following script can be used to generate that file. Choose the counters accordingly to the situation: i, j, k, gpu.
File: script.sh
# Este script genera un (CPUresources.cmd) que contiene
# las líneas necesarias para agregar los recursos GPU de un
# nodo a la BD de OAR
# En el caso de guane, hay 24 cores por nodo y 8 GPUs por nodo
# Entonces se asigna un GPU cada 3 cores.
#!/bin/bash
i=169
j=170
k=171
gpu=57
while [ $gpu -lt 65 ]
do
echo "oarnodesetting --sql \"core=$i\" -p gpu=YES -p gpunum=$gpu -p gputype=M2075" >> GPUresources.cmd
echo "oarnodesetting --sql \"core=$j\" -p gpu=YES -p gpunum=$gpu -p gputype=M2075" >> GPUresources.cmd
echo "oarnodesetting --sql \"core=$k\" -p gpu=YES -p gpunum=$gpu -p gputype=M2075" >> GPUresources.cmd
i=`echo $i + 3 | bc`
j=`echo $j + 3 | bc`
k=`echo $k + 3 | bc`
gpu=`echo $gpu + 1 | bc`
done
5. Add the resources with the following command:
source GPUresources.cmd
