Deep Learning Workstations
From Robin
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* Install CUDA 8.0 and CUDnn 6.0 for Tensorflow 1.4 | * Install CUDA 8.0 and CUDnn 6.0 for Tensorflow 1.4 | ||
- | + | = Setup SSH Server = | |
* The SSH server config (/etc/ssh/sshd_config) should be hardened to prevent brute force password attacks. | * The SSH server config (/etc/ssh/sshd_config) should be hardened to prevent brute force password attacks. |
Revision as of 15:40, 15 January 2018
Contents |
Deep Learning Workstations
We have shared workstations for projects needing serious GPU and CPU power while retaining physical access to a computer.
Most interesting are the four Dell Alienware computers from January 2018, here are their details and responsible staff for ongoing record keeping:
- Aurora R7 - Intel i7 8700K (6-core), 2x Nvidia GTX1080ti (UiO: 113616). Justas/Zia/Weria
- hostname:
- URL:
- WLAN: D8:9E:F3:7A:84:B7
- ETH: 9C:30:5B:13:AF:33
- Aurora R7 - Intel i7 8700K (6-core), 2x Nvidia GTX1080ti (UiO: 113615). Charles/Kai/Tønnes
- hostname:
- URL:
- WLAN: D8:9E:F3:7A:7E:D1
- ETH: 9C:30:5B:13:C5:69
- Aurora R7 - Intel i7 8700K (6-core), 2x Nvidia GTX1070ti (UiO: 113617). Vegard/Masterstudenter
- hostname:
- URL:
- WLAN: D8:9E:F3:7A:46:08
- ETH: 9E:30:5B:13:C5:8B
- Area 51 R3 - AMD Threadripper 1950x (16-core), 1x Nvidia GTX1070ti (UiO: 113614). Jørgen etc.
- hostname:
- URL:
- WLAN: 9C:30:5B:13:C5:71
- ETH1: 30:9C:23:2A:EB:39
- ETH2: 30:9C:23:2A:EB:38
We also have older workstations:
- Deep Thinker: Intel..., 2x Nvidia GXT1080. Charles/Justas/Masterstudenter
- hostname: deepthinker
- url: deepthinker.onthewifi.com
Setting up the workstations
As a rule, shared systems should be able to dual-boot between Windows 10 and Ubuntu.
- For the Dell systems, first shrink the main NTFS partition to allow an Ubuntu system partition.
- The shared (spinning) disk can stay as NTFS.
- Ubuntu 17.10 is ok for Deep Learning / how about for robotics applications?
Tensorflow
- Install tensorflow-gpu to use GPUs.
- Tensorflow requires specific versions of CUDA and CUDnn
- For Tensorflow 1.4 (current release as of 9/1/2018): Need CUDA 8, CUDnn 6
- For Tensorflow 1.5 (prerelease as of 9/1/2018) - works with CUDA 9, CUDnn 7 (latest).
Ubuntu 16.04 Setup
Install Ubuntu 16.04, do not turn Secure Boot off.
- Shrink Windows NTFS volume in Disk Management
- Remove graphics cards
- Install Ubuntu following these instructions
- Install Nvidia graphics driver from PPA repository.
- Put graphics cards back in.
- verify that you can boot into Windows and Ubuntu
- Ubuntu sometimes freezes on shutdown due to an I2C driver, which can be blacklisted
- If Ubuntu doesn't login and graphics are weird, probably using unsigned Nvidia driver, use this script to sign kernel modules. - if this path is taken, modules need to be signed against any new future kernels.
- Install CUDA 8.0 and CUDnn 6.0 for Tensorflow 1.4
Setup SSH Server
- The SSH server config (/etc/ssh/sshd_config) should be hardened to prevent brute force password attacks.
- Broadly, follow these instructions to disable password access and use fail2ban and deny hosts
- Regular users should copy their public key to the machine in person and add it to ~/.ssh/authorized_keys
- ssh-copy-id won't work if password access is turned off :-\