From 503945e7c3f82910f6eaef52ccddb49f5631c2f2 Mon Sep 17 00:00:00 2001 From: Claude Date: Sat, 22 Aug 2026 03:46:06 +0000 Subject: [PATCH] docs(ai-stack): correct CUDA deprecation status, add Tesla power/cooling note CUDA 13 already dropped Pascal/Volta (not a future warning anymore) - call out pinning the driver branch instead. Also flag the 8-pin CPU/EPS12V power connector and passive cooling on Tesla PCIe cards, since it trips up anyone repurposing one in a tower case. --- services/ai-stack.md | 23 +++++++++++++++++++---- 1 file changed, 19 insertions(+), 4 deletions(-) diff --git a/services/ai-stack.md b/services/ai-stack.md index 1847092..3592e11 100644 --- a/services/ai-stack.md +++ b/services/ai-stack.md @@ -77,10 +77,25 @@ flash-attention-class kernel path. | Pascal (2016) | P100 16GB / P40 24GB | 16-24GB HBM2/GDDR5 | No | SD1.5 fine; SDXL runs but slow — no tensor cores at all, weak/emulated FP16 (worse on the P40 than the P100) | Same VRAM math as Ampere/Volta at matched capacity (P40 24GB ≈ 30B Q4), but noticeably slower tokens/sec | 32B coder Q4 fits the P40 24GB capacity-wise; fine for batch/background, not snappy interactive autocomplete | | Maxwell (2014) | M40 / M60 24GB | 8-24GB GDDR5 | No | Impractical — SD1.5 only, very slow; no real FP16 tensor path | 7B-13B Q4 runs but slow | 7B-class coder models only — a novelty, not a daily driver | -NVIDIA's CUDA 12.9 release notes flag Maxwell, Pascal, and Volta as the last -architectures the *next* major toolkit will support — existing CUDA 12.x -builds keep working, but factor this in before buying used Pascal/Volta -hardware today. +**CUDA 13 has already dropped Pascal/Volta** (this happened, it's not a future +warning anymore) — pin the host driver to an LTS/LTSB branch that still lists +Volta as supported (check `ubuntu-drivers devices`' recommendation rather than +blindly taking the newest branch) before relying on one of these cards. Docker +GPU passthrough only needs the host *driver* to recognize the card — prebuilt +inference images (Ollama, ComfyUI, etc.) already bundle whatever CUDA runtime +they need — so this is a driver-branch choice at install time, not something +`require_docker` pins for you (it installs Docker/Compose only; NVIDIA +driver + `nvidia-container-toolkit` are still on you to install first). + +**Tesla-card power connector — don't assume standard PCIe.** V100/P100/P40/M40 +PCIe cards take an 8-pin **CPU/EPS12V** connector, not the 6+2-pin PCIe +connector a normal GPU uses — a standard PCIe cable will not plug in. Get the +dongle/adapter (splits a PCIe 8-pin into EPS12V, or use a real EPS cable) and +never daisy-chain both 8-pin rails off one PSU cable/splitter — use two +separate cable runs. These cards are also passively cooled (built for server +chassis airflow, no onboard fan) — a tower case needs a shroud + dedicated +fan blowing through the heatsink fins, and there's no display output, which +is a non-issue on a headless box like this but worth knowing going in. **MoE models are the exception that gives Pascal/Volta real life for coding.** The "coding" column above assumes dense models, where token speed tracks the