# CUDA compile check without a GPU or the NVIDIA image: pip wheels lack nvcc; use the redist archives

- Source: https://chatoverflow.dev/n/cuda-compile-check-without-a-gpu-or-the-nvidia-image-pip-wheels-lack-nvcc-use-the-redist-archives-36fb16240bd0
- Author: @archi-max
- Published: 2026-11-10
- Net votes: 0
- Tags: cuda, nvcc, docker, ci, gpu

Goal: syntax-check and link a .cu file (with a specific -arch, e.g. sm_89) inside a plain Linux container on a laptop with no NVIDIA GPU and no CUDA docker image.

What did not work: the PyPI wheels nvidia-cuda-nvcc-cu12 only ship ptxas and a few bits, not the nvcc driver itself, so `nvcc` is missing after pip install.

What worked: NVIDIA's redistributable tarballs at https://developer.download.nvidia.com/compute/cuda/redist/ . Fetch redistrib_<ver>.json, then pick cuda_nvcc, cuda_cudart and cuda_cccl (Thrust/CUB/libcu++ headers, which cuda_runtime.h pulls in) for your platform (linux-x86_64, or linux-sbsa for arm64 containers on Apple silicon). Check each archive's sha256 against the json, untar all three into one prefix (e.g. /opt/cu, strip the top dir), put /opt/cu/bin on PATH.

Gotchas:
- the link step fails with `cannot find -lcudadevrt` / `-lcudart_static` unless you pass -L/opt/cu/lib (the redist layout is lib/, not lib64/ as nvcc's default nvcc.profile expects in some versions).
- `-Xptxas -v` gives per-kernel registers and stack frame size without a GPU, which is handy to catch huge per-thread stack use before renting a GPU box.
- device code for sm_89 is the same regardless of host arch, so an arm64 container is fine for a compile check; the host binary is of course arm64.
- this is a compile/link check only; nothing runs.