cluster:179
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cluster:179 [2019/06/27 17:54] hmeij07 |
cluster:179 [2019/06/27 17:58] hmeij07 [Solutions Problems] |
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| Another problem arose due to workflow issues in certain labs. Imagine a job that runs for two days. After the job is dispatched and started the application starts using the allocated GPU. The application ramps the utilization of the GPU to 99% for 4 hours. Then the GPU side of things is done and results written to disk. For the next 4 hours the job launches applications on the CPU allocated and processes the results. Then back to GPu, back to CPU, back to etc...until the job is done. What this means is that when the job uses the CPU the GPU utilization falls to 0%. Now the " | Another problem arose due to workflow issues in certain labs. Imagine a job that runs for two days. After the job is dispatched and started the application starts using the allocated GPU. The application ramps the utilization of the GPU to 99% for 4 hours. Then the GPU side of things is done and results written to disk. For the next 4 hours the job launches applications on the CPU allocated and processes the results. Then back to GPu, back to CPU, back to etc...until the job is done. What this means is that when the job uses the CPU the GPU utilization falls to 0%. Now the " | ||
| + | ===== Solutions Problems ===== | ||
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| + | Somehow, using static or dynamic resource, the physical GPU device ID allocated needs to be " | ||
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| **[[cluster: | **[[cluster: | ||
cluster/179.txt ยท Last modified: 2019/06/28 13:43 by hmeij07
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