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computers [2017/03/06 16:40]
mai [Computers]
computers [2019/07/03 23:44] (current)
mai
Line 4: Line 4:
 ===== Computers ===== ===== Computers =====
  
-|Name of the computer |Brand |Operating System |Type of system (bits) |RAM (Go) | Processor |disk memory | hardware | used for | +| Name of the computer ​ | Brand               ​| Operating System ​ | Type of system (bits) ​ | RAM (Go)  | Processor ​               | disk memory ​ | hardware ​     | used for           ​
-|PC-EQI05710 |Dell Latitude |Windows 7 |32 |8 |Intel Core i5-33220M |214/300 | 2 USB3 ports  |Poppy and kinect2 ​  +| PC-EQI05710 ​          ​| Dell Latitude ​      ​| Windows 7         ​| 32                     ​| 8         ​| Intel Core i5-33220M ​    ​| 214/​300 ​     | 2 USB3 ports  | Poppy and kinect2  ​| 
-|ihsev |Dell Lattude E6410 |Ubuntu 14.04 LTS |32 | |Intel Core i5 CPU M 520 | 158 | USB2 only |Nao | +[[ihsev laptop|ihsev]] ​                | Dell Lattude E6410  | Ubuntu 14.04 LTS  | 32                     ​          ​| Intel Core i5 CPU M 520  | 158          | USB2 only     ​| Nao                
-|greiner |Dell PowerEdge | Ubuntu | | 128 | 32 coeurs | | server only |cuda, theano |   +[[greiner]]               | Dell PowerEdge ​     | Ubuntu ​                                  | 128       ​| 32 coeurs ​               193G            ​| server only. Has 2 [[https://​www.nvidia.fr/​data-center/​tesla-k80/​|GPU Nvidia Tesla K80]]   | cuda, theano ​      ​
-|helen | | Ubuntu | | | | | server only | ROS |+[[gazebo server|gazebo]] ​              ​| ​                    | Ubuntu ​           64                     128       32 coeurs ​               ​196G         | server only   ​| ROS                |
    
 +===== Servers =====
 +==== Greiner ====
 +Greiner has two GPUs.
 +
 +login to greiner:
 +    * ip : ssh -X login@greiner.enstb.org ​
 +    * login : ton_login_ecole ​
 +
 +check the sate of the gpu with command
 +   ​nvidia-smi
 +
 +For geiner, the output is : 
 +<​code>​
 ++-----------------------------------------------------------------------------+
 +| NVIDIA-SMI 396.24 ​                ​Driver Version: 396.24 ​                   |
 +|-------------------------------+----------------------+----------------------+
 +| GPU  Name        Persistence-M| Bus-Id ​       Disp.A | Volatile Uncorr. ECC |
 +| Fan  Temp  Perf  Pwr:​Usage/​Cap| ​        ​Memory-Usage | GPU-Util ​ Compute M. |
 +|===============================+======================+======================|
 +|   ​0 ​ Tesla K80           ​Off ​ | 00000000:​06:​00.0 Off |                    0 |
 +| N/A   ​50C ​   P0    58W / 149W |      0MiB / 11441MiB |      0%      Default |
 ++-------------------------------+----------------------+----------------------+
 +|   ​1 ​ Tesla K80           ​Off ​ | 00000000:​07:​00.0 Off |                    0 |
 +| N/A   ​36C ​   P0    74W / 149W |      0MiB / 11441MiB |    100%      Default |
 ++-------------------------------+----------------------+----------------------+
 +                                                                               
 ++-----------------------------------------------------------------------------+
 +| Processes: ​                                                      GPU Memory |
 +|  GPU       ​PID ​  ​Type ​  ​Process name                             ​Usage ​     |
 +|=============================================================================|
 +|    0     ​93895 ​     C   ​python3 ​                                   10941MiB |
 +|    1     ​93895 ​     C   ​python3 ​                                   10863MiB |
 ++-----------------------------------------------------------------------------+
 +</​code>​
 +
 +Par défaut, Tensorflow alloue l'​ensemble de la mémoire GPU au programme, même s'il n'en nécessite que 10%.
 +Il existe une option permettant d'​allouer seulement la mémoire GPU nécessaire.
 +Il faut ajouter les lignes suivantes:
 +<​code>​
 +   ​config = tf.ConfigProto()
 +   ​config.gpu_options.allow_growth = True
 +   sess = tf.Session(config=config)
 +
 +</​code>​
 +
 +==== Gazebo ====
 +
 +Login to gazebo:
 +    * you must first connect to the School VPN. Official instructions are on https://​intranet.telecom-bretagne.eu/​page.php?​idContenu=5061 :
 +        * On linux you can install `vpnc` and use the following configuration in `/​etc/​vpnc/​tb.conf`:​
 +          * <​code>​
 +IKE DH Group dh2
 +IPSec gateway 192.108.116.206
 +IPSec ID vpnrire
 +IPSec secret rire
 +Xauth username</​code>​
 +          * Then run `sudo vpnc tb` to start the vpn
 +        * On macos, Open up your System Preferences and select "​Network"​. Click on the little + button at the bottom of the window to create a new connection.Pick "​VPN"​ for the Interface and set the VPN type to "Cisco IPSec"​. It doesn'​t matter what you set as the service name. Click on "​create"​. As Server address, input "​192.108.116.206"​ and in the account name and passwords use your login and password for the school identification. As authentication settings, input the group name "​vpnrire"​ and the shared secret is "​rire"​.
 +    * You can now ssh to gazebo like this:
 +        * `ssh -X login@gazebo.enstb.org`
 +        * where login: ton_login_ecole ​
 +
 +Update 20180802: Where is the desktop??
 +
 +==== Backup1 ====
 +
 +To login, you need first to send Jerome or Mai your ssh public key. Then, you can connect by ssh laborobo@backup1.enstb.org
 +
 +Contents:
 +
 +  * VM (Virtual machines)
 +    * UbuntuRobot : Ubuntu virtual machine with gazebo (turtlebot) and ros installed. Description in [[simulatorgazebo|Simulateur Gazebo]]
 +  * Keraal
  • computers.1488818459.txt.gz
  • Last modified: 2019/04/25 14:08
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