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tutorial:torque [2017/03/19 22:03] afo214 |
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===== Options ===== | ===== Options ===== | ||
- | * '' | + | ^ Option |
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- | See [[http:// | + | You can find detailed information |
+ | <note tip>You need to use option '' | ||
===== Monitoring and Removing jobs ===== | ===== Monitoring and Removing jobs ===== | ||
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<note tip>Use **-singleCompThread** [[https:// | <note tip>Use **-singleCompThread** [[https:// | ||
- | ==== Running | + | ==== Running |
- | In order to run a gurobi job, you need to use " | + | In order to run solvers (such as Gurobi/ |
< | < | ||
+ | |||
+ | This flag enables the solver to find necessary authentication information. | ||
==== Interactive Jobs ==== | ==== Interactive Jobs ==== | ||
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However, first you have to have a permission to use GPU (given by Prof. Takac) -- this is just formality to allow to certain users to use video driver on polyp30 | However, first you have to have a permission to use GPU (given by Prof. Takac) -- this is just formality to allow to certain users to use video driver on polyp30 | ||
+ | |||
+ | If you are using TensorFlow in Python, you can set the limit on amount of GPU memory using: | ||
+ | < | ||
+ | config_tf.gpu_options.per_process_gpu_memory_fraction = p</ | ||
+ | in which < | ||
==== Running MPI and Parallel Jobs ==== | ==== Running MPI and Parallel Jobs ==== | ||
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+ | ==== Tensorflow with GPU ==== | ||
+ | To use tensorflow with a specific GPU, say GPU 1, you can simply set | ||
+ | <code bash> | ||
+ | export CUDA_VISIBLE_DEVICES=1 | ||
+ | </ | ||
+ | and then schedule your jobs with Torque to perform experiments on GPU 1. |