noisedestroyers
228fe8d1ac
apt's btop on 24.04 is 1.3.x, which has no AMD GPU monitoring. 1.4+ adds it but requires C++23, which gcc-13 (24.04 default) doesn't fully support. Plan: - Add ubuntu-toolchain-r/test PPA, install g++-14 (C++23-capable). - Add librocm-smi-dev to ROCm host diagnostics — btop dlopens librocm_smi64 at runtime; the headers are needed at compile time. - Drop btop from apt list, build from a pinned BTOP_VERSION tag with GPU_SUPPORT=true CXX=g++-14 -j; install to /usr/local/bin. - Idempotent — only rebuilds if installed version doesn't match. After deploy: btop → Esc → Options → "show_gpu_info" → On to enable the GPU panel. Also clean up TODO.md — the box is on 24.04 (noble), not 26.04. The libxml2 ABI mismatch / "ROCm gap" section was stale. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
37 lines
1.5 KiB
Markdown
37 lines
1.5 KiB
Markdown
# TODO
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## ROCm / vLLM on Strix Halo (gfx1151)
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The Framework Desktop runs **Ubuntu 24.04 LTS (noble)**, which aligns
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with AMD's ROCm 7.x packaging. The deploy installs `rocminfo` and
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`librocm-smi-dev` host-side; heavier ROCm bits (full HIP toolchain,
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device-mapped libraries) still run inside containers that ship their
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own ROCm stack. The host stays slim by design.
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### Open questions
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- **Does `rocm/vllm:latest` actually run on Strix Halo's iGPU?** vLLM's
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AMD support officially targets datacenter cards (MI300X / gfx942).
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gfx1151 (RDNA 3.5 consumer) is a different ISA. If the stock image
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doesn't initialize the device, try `rocm/vllm-dev:nightly` or build
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from source against ROCm 7.x with `-DAMDGPU_TARGETS=gfx1151`.
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### If you ever want full host-side ROCm
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For native ROCm work on the host (compiling HIP kernels, full toolchain):
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1. Bump `ROCM_VERSION` and `AMDGPU_INSTALL_DEB` in
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`pyinfra/framework/deploy.py` to the latest release.
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2. Add a step that runs `amdgpu-install -y --usecase=rocm --no-dkms`
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(currently avoided to stay slim — ~25 GB toolchain).
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3. `./run.sh`.
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For container-only workflows (current default), no action is needed —
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container images update independently of the host.
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## Pick a coding model (StrixHaloSetup Phase 6)
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Open question — research current Strix Halo benchmarks before
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committing. Candidates: Qwen3-Coder, DeepSeek-Coder-V3.x, GLM-4.6,
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Devstral, Kimi-K2. Track Kimi Linear separately via the weekly routine
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referenced in `StrixHaloSetup.md`.
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