CubelaPetarandClaude Fable 5
43054f32b8
- run.yml: base plays (geerlingguy.security) for jira and git; gpu01 play with security + docker + nvidia_gpu - roles/nvidia_gpu: driver pinned >=580 (Blackwell), CUDA repo, container toolkit incl. the nvidia-ctk runtime configure step - manuals/20260714-nvidia-driver-install.md: dated per convention, corrected (pinned -server driver instead of autoinstall+cuda-drivers mix, toolkit optional, added missing nvidia-ctk/docker restart step) - gpu01 folder: planning docs under notes/, runbooks under manuals/, scripts/; convention documented in CLAUDE.md - scripts/share-analysis.ps1: read-only SMB share analysis for the Windows server (projektplan §2.1) - TODO.md: Phase-0 pre-work items from the projektplan Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
32 lines
1.2 KiB
Markdown
32 lines
1.2 KiB
Markdown
# phy-z-srv-gpu01
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GPU server for AI/ML workloads. Hardware is ordered/assessed; OS setup and configuration are the next step.
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| IP | 192.168.66.69 (planned) |
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| Ansible group | `phy_z_srv_gpu01` |
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| Status | planned — not yet configured |
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## Hardware
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HPE ProLiant DL380 Gen12, 2× Intel Xeon 6714P (8-core, 4.0 GHz), 128 GB RAM,
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NVIDIA RTX PRO 6000 96 GB, 2× 960 GB NVMe SSD, redundant PSU — full BOM in [HW.md](HW.md).
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## Planning notes
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- [Hardware assessment (2026-07-06)](notes/20260706-hardware-assessment.md)
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- [Software assessment (2026-07-06)](notes/20260706-software-assessment.md)
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- [Deep dive (2026-07-07)](notes/20260707-deep-dive.md)
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- [Project plan for the setup (2026-07-10)](notes/20260710-projektplan.md) — start here when the server arrives
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Open pre-work items are tracked in the repo-root [TODO.md](../../TODO.md).
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## Runbooks
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- [NVIDIA driver, CUDA repo & container toolkit (2026-07-14)](manuals/20260714-nvidia-driver-install.md) — automated by the Ansible role `nvidia_gpu`
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## Scripts
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- [share-analysis.ps1](scripts/share-analysis.ps1) — read-only SMB share analysis (projektplan §2.1); run on a Windows machine with read access to the shares
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