check_workload_cpu_gpu
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check_workload_cpu_gpu [2016/06/06 15:49] – created hj | check_workload_cpu_gpu [2017/07/10 20:06] (current) – hj | ||
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- | ====== Check CPUs workload: | + | === Check CPUs workload: === |
- | | + | - We have a simple script for you to check the workload of all machines, you may run: |
+ | - Run Linux ' | ||
+ | - If your program consumes lots of memory (over 10G), DON’T submit it more than once to a single machine. | ||
- | /// | + | === Check GPUs workload: === |
- | Every time when you submit | + | - We have a simple script |
+ | | ||
- | - Run Linux ' | ||
- | |||
- | - If your program consumes lots of memory (over 10G), DON’T submit it more than once to a single machine. | ||
+ | In most machine learning framework, the first GPU is picked by default. Tensorflow, for example, will pre-allocate a chunk of memory on EVERY SINGLE GPU if you don’t explicitly mask the unneeded. Masking can be done by, for example “**setenv CUDA_VISIBLE_DEVICES 1**”, if you only want to expose the second GPU (GPU is 0-indexing). | ||
+ | {{: |
check_workload_cpu_gpu.1465228192.txt.gz · Last modified: 2016/06/06 15:49 by hj