Deep Learning Workstations

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Revisjon per 9. jan 2018 kl. 19:28 av Charlepm (Diskusjon | bidrag)
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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).
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