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The gpu_requeue partition includes 30 32 GPUs: 28 single precision RTX 6000 cards and , 2 double precision Tesla M40 cards and 2 A100 cards.
To list current information about all the nodes and cards available for a specific partition use the command sinfo --Format=nodehost,available,memory,statelong,gres:20 -p <partition> for example:
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login02:~ sinfo --Format=nodehost,available,memory,statelong,gres:20 -p gpu,gpu_quad,gpu_requeue HOSTNAMES AVAIL MEMORY STATE GRES compute-g-16-175 up 257548 mixed gpu:teslaM40:4 compute-g-16-176 up 257548 mixed gpu:teslaM40:4 compute-g-16-177194 up 257548 mixed gpu:teslaK80:8 compute-g-16-194254 up 257548373760 mixed gpu:teslaK80teslaV100:84 compute-g-16-254255 up 373760 mixed gpu:teslaV100:4 compute-g-16-255177 up 257548 373760 idle mixed gpu:teslaV100teslaK80:48 compute-g-17-145146 up 770000 idlemixed gpu:rtx8000:10 compute-g-17-146147 up 770000383000 idle mixed gpu:rtx8000teslaV100s:104 compute-g-17-147148 up 383000 idle mixed gpu:teslaV100s:4 compute-g-17-148149 up 383000 idle mixed gpu:teslaV100s:4 compute-g-17-149150 up 383000 idlemixed gpu:teslaV100s:4 compute-g-17-150151 up 383000 idlemixed gpu:teslaV100s:4 compute-g-17-151152 up 383000 idlemixed gpu:teslaV100s:4 compute-g-17-152153 up 383000 idle mixed gpu:teslaV100srtx8000:43 compute-g-17-153154 up 383000 idle mixed gpu:rtx8000:3 compute-g-17-154155 up 383000 idle mixed gpu:rtx8000:3 compute-g-17-155156 up 383000 idlemixed gpu:rtx8000:3 compute-g-17-156157 up 383000 idlemixed gpu:rtx8000:3 compute-g-17-157159 up 383000 idlemixed gpu:rtx8000:3 compute-g-17-158160 up 383000 idle mixed gpu:rtx8000:3 compute-g-17-159161 up 383000 idlemixed gpu:rtx8000:3 compute-g-17-160145 up 383000770000 idleallocated gpu:rtx8000:310 compute-g-17-161158 up 383000 idledown gpu:rtx8000:3 compute-g-16-197 up 257548 mixed gpu:teslaM40:2 compute-gc-17-247245 up 383000 mixed gpu:rtx6000:810 compute-ggc-1617-197247 up 257548383000 idlemixed gpu:teslaM40rtx6000:28 compute-gc-17-245249 up 3830001000000 idlemixed gpu:rtx6000a100:102 compute-gc-17-246 up 383000 idle gpu:rtx6000:10 |
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The gpu_quad partition is open to any users working for a PI with a primary or secondary appointment in a pre-clinical department; to run jobs on the gpu_quad partition use the flag -p gpu_quad. If you work at an affiliate institution but are collaborating with an on-Quad PI, please contact Research Computing to gain access.
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Starting from July 1st 2021 the gpu_requeue partition will be available only to users working for a PI with a primary or secondary appointment in a pre-clinical department. |
For detailed information about the gpu_requeue see O2 GPU Re-Queue Partition.
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