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gpu [2017/03/16 17:10]
kocmanek [Basic commands]
gpu [2017/07/17 09:18]
kocmanek [Performance tests]
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 ===== Servers with GPU units ===== ===== Servers with GPU units =====
  
-| machine | GPU; [[https://en.wikipedia.org/wiki/CUDA#Supported_GPUs|Capability]] [cc]  | cores | GPU RAM | Comment | +| machine                    | GPU; [[https://en.wikipedia.org/wiki/CUDA#Supported_GPUs|Capability]] [cc]  | cores | GPU RAM | Comment 
-| titan-gpu  | GeForce GTX Titan Z; cc3.5 | 2 | 6 GB each core |        +| titan                      | GeForce GTX 1080 Ti; cc6.1 | 1  | 11 GB           |  
-| twister1   | Tesla K40ccc3.5          | 1 | 12 GB          |        | +| titan-gpu                  | GeForce GTX Titan Z; cc3.5 | 2  | 6 GB each core   
-twister2   | Tesla K40ccc3.5          | 1 | 12 GB          |        | +| twister1; twister2; kronos | Tesla K40c; cc3.5          | 1  | 12 GB            
-kronos-dev | Tesla K40c; cc3.5          | 1 | 12 GB                 +| iridium                    | Quadro K2000; cc3.0        | 1  | 2 GB             
-| iridium    | Quadro K2000; cc3.0        | 1 | 2 GB                  +| victoria; arc              | GeForce GT 630; cc3.0      | 1  | 2 GB            | desktop machine | 
-| victoria   | GeForce GT 630cc3.0      | 1 | 2 GB           | Ondrej Bojar's desktop machine | +| athena                     | GeForce GTX 1080; cc6.1    | 1  | 8 GB            | Tom's desktop machine | 
-arc        | GeForce GT 630; cc3.0      | 1 | 2 GB           Ales'desktop machine | +| dll1; dll2                 | GeForce GTX 1080; cc6.1    | 8  | 8 GB each core  |  | 
-| athena     | GeForce GTX 1080; cc6.1    | 1 | 8 GB           | Tom's desktop machine | +dll3; dll4; dll5           | GeForce GTX 1080 Ti; cc6.1 | 10 11 GB each core |  |
-| dll1     | GeForce GTX 1080; cc6.1    | 8 | 8 GB each core |  | +
-dll2     | GeForce GTX 1080; cc6.1    GB each core |  |+
  
 not used at the moment: GeForce GTX 570 (from twister2) not used at the moment: GeForce GTX 570 (from twister2)
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   * Ondřej Plátek - granted (2015)   * Ondřej Plátek - granted (2015)
   * Jan Hajič jr. - granted (early 2016)   * Jan Hajič jr. - granted (early 2016)
-  * Jindra Helcl - planning to apply (fall 2016) 
  
  
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 For testing and using the cluster interactively you can use qrsh (this should not be used for long running experiments since the console is not closed on the end of the experiment). Following command will assign you a GPU and creates interactive console. For testing and using the cluster interactively you can use qrsh (this should not be used for long running experiments since the console is not closed on the end of the experiment). Following command will assign you a GPU and creates interactive console.
  
-  qrsh -q gpu.q -l gpu=1 -pty yes bash+  qrsh -q gpu.q -l gpu=1,gpu_ram=2G -pty yes bash
      
 For running experiments you must use qsub command: For running experiments you must use qsub command:
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   qsubmit --gpumem=2G --queue="gpu.q" WHAT_SHOULD_BE_RUN   qsubmit --gpumem=2G --queue="gpu.q" WHAT_SHOULD_BE_RUN
      
 +It is recommended to use priority -100 if you are not rushing for the results and don't need to leap over your colleagues jobs.
 ==== Basic commands ==== ==== Basic commands ====
  
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   /usr/local/cuda/samples/1_Utilities/deviceQuery/deviceQuery   /usr/local/cuda/samples/1_Utilities/deviceQuery/deviceQuery
     # shows CUDA capability etc.     # shows CUDA capability etc.
 +    
 +=== Select GPU device ===
 +
 +Use variable CUDA_VISIBLE_DEVICES to constrain tensorflow to compute only on the selected one. For the use of first GPU use (GPU queue do this for you):
 +  export CUDA_VISIBLE_DEVICES=0
 +
 +To list available devices, use:
 +  /opt/cuda/samples/1_Utilities/deviceQuery/deviceQuery | grep ^Device
 +
 ===== Performance tests ===== ===== Performance tests =====
  
 * [[http://www.trustedreviews.com/nvidia-geforce-gtx-1080-review-performance-benchmarks-and-conclusion-page-2| 980 vs 1080 vs Titan X (not the Titan Z we have)]] * [[http://www.trustedreviews.com/nvidia-geforce-gtx-1080-review-performance-benchmarks-and-conclusion-page-2| 980 vs 1080 vs Titan X (not the Titan Z we have)]]
  
-In the following table is the experiment conducted by Tom Kocmi. You can replicate experiment: /a/merkur3/kocmanek/Projects/GPUBenchmark (you will need to prepare environment of TensorFlow11 or use my ANACONDA)+In the following table is the experiment conducted by Tom Kocmi. You can replicate experiment: /a/merkur3/kocmanek/Projects/GPUBenchmark (you will need to prepare environment of TensorFlow11 or use my ANACONDA). The benchmark uses 2GB model.
  
 | machine | Setup; CPU/GPU; [[https://en.wikipedia.org/wiki/CUDA#Supported_GPUs|Capability]] [cc] | Walltime | Note | | machine | Setup; CPU/GPU; [[https://en.wikipedia.org/wiki/CUDA#Supported_GPUs|Capability]] [cc] | Walltime | Note |
 | athena     | GeForce GTX 1080; cc6.1            |    9:55:58 | Tom's desktop  | | athena     | GeForce GTX 1080; cc6.1            |    9:55:58 | Tom's desktop  |
 | dll2       | (2 GPU) GeForce GTX 1080; cc6.1    |   10:19:40 | with CUDA_VISIBLE_DEVICES=0 | | dll2       | (2 GPU) GeForce GTX 1080; cc6.1    |   10:19:40 | with CUDA_VISIBLE_DEVICES=0 |
 +| titan      | GeForce GTX 1080 Ti                |   10:45:11 | (new result with correct CUDA version) |
 | dll1       | (2 GPU) GeForce GTX 1080; cc6.1    |   12:34:34 | Probably only one GPU was used | | dll1       | (2 GPU) GeForce GTX 1080; cc6.1    |   12:34:34 | Probably only one GPU was used |
 | dll2       | (2 GPU) GeForce GTX 1080; cc6.1    |   13:01:05 | Only one GPU was used | | dll2       | (2 GPU) GeForce GTX 1080; cc6.1    |   13:01:05 | Only one GPU was used |
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 | arc        | GeForce GT 630; cc3.0              |  103:42:30 | (approximated after 66 hours) | | arc        | GeForce GT 630; cc3.0              |  103:42:30 | (approximated after 66 hours) |
 | lucifer4   | 8x cores CPU                        134:41:22 |  | | lucifer4   | 8x cores CPU                        134:41:22 |  |
-| victoria   | GeForce GT 630; cc3.0              |        --- | never run, same GPU as Arc | 
  
  
-===== Installed toolkits ===== +=== Second Benchmark ===
- +
-//This should mention where each interesting toolkit lives (on a particular machine).// +
- +
-==== TensorFlow ==== +
- +
-[[https://redmine.ms.mff.cuni.cz/projects/mmmt/repository/revisions/6a064187fc6959db9b77cf2d5350c5f4918a8067/entry/prepare_env.sh|This script]] installs TensorFlow 0.7.1 (and all other dependencies we need for Multimodal Translation) into `tf' and `tf-gpu' virtual environments. The GPU environment can be loaded by calling <code>source tf-gpu/bin/activate-gpu</code> +
- +
-OP: I created [[https://gist.github.com/oplatek/323b63b8f116cd3d78c0f492f78cc289|script]] which install Tensorflow 0.8 and test it if it uses GPU. TF is installed into `user` or `global` installation either for `python3.4` or `python2.7` +
- +
-=== Select GPU device === +
- +
-Use variable CUDA_VISIBLE_DEVICES to constrain tensorflow to compute only on the selected one. For the use of first GPU use: +
-<code>export CUDA_VISIBLE_DEVICES=0</code> +
- +
-To list available devices, use: +
-<code>/opt/cuda/samples/1_Utilities/deviceQuery/deviceQuery | grep ^Device</code>+
  
 +The previous benchmark only compares the speed of processing units within the GPUs and do not take into account the size of memory. Therefore I have conducted another benchmark, this time for each graphic card I have increased the batch size as much as possible so the model still could fit into the GPU (the previous benchmark had batch size 20). This way the results should be more representative of the power for each GPU.
  
 +| GPU; Cuda capability       | GPU RAM |  Walltime | Batch size | Machine |
 +| Tesla K40c; cc3.5          |   12 GB |                 2500 | kronos |
 +| GeForce GTX 1080 Ti; cc6.1 |   11 GB |  00:55:56 |       2300 | dll5 |
 +| GeForce GTX 1080; cc6.1    |    8 GB |  01:10:57 |       1700 | dll1 |
 +| GeForce GTX 1080; cc6.1    |    8 GB |                 1500 | athena (no virtualization, less memory due to the X) |
 +| GeForce GTX Titan Z; cc3.5 |    6 GB |  02:20:47 |       1100 | titan-gpu |
 +| Quadro K2000; cc3.0        |    2 GB |  28:15:26 |         50 | iridium |
  
 ===== Links ===== ===== Links =====

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