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[BUG]: Program.compile("ptx") fails on machines without a CUDA driver, although NVRTC does not need one

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
70/100
Issue type
Bug
Clarity
Clearly specified
Activity status
Active
Tech stack
python
Domain
compilers

Research direction

Start in cuda/core/_program.pyx at _can_load_generated_ptx() (around line 815) and the cache-hit branch of Program.compile (~line 1192); the raising call is driver_version() in cuda/core/_utils/version.pyx, which needs libcuda. Catch the DynamicLibNotFoundError and skip the loadability warning instead of failing, mirroring the cubin path. Reproduce with the snippet on a driverless machine and check existing cuda.core program tests; done means PTX compiles without a driver and a warning (or silent skip) replaces the error.

Written by the indexing model from the issue text.

Description

triage
Is this a duplicate?
Type of Bug

Runtime Error

Component

cuda.core

Describe the bug

On a Linux machine with no NVIDIA driver installed (a GitHub Actions ubuntu runner), compiling a Program to PTX with the NVRTC backend raises DynamicLibNotFoundError for libcuda.so.1. Compiling the same source to cubin with an explicit arch works on the same machine, so NVRTC itself is available.

The failure comes from the loadability check that runs before PTX compilation. _can_load_generated_ptx() calls driver_version(), which calls cuDriverGetVersion and needs libcuda. The check only decides whether to emit a RuntimeWarning, but when the driver library is missing it raises instead, and the whole compile fails. The same check is on the cache hit path in Program.compile.

This matters for CI jobs that compile kernels to PTX without a GPU, for example to inspect the generated PTX in tests. My workaround was to call cuda.bindings.nvrtc directly with the flags from ProgramOptions.as_bytes("nvrtc", "ptx"), which works without a driver.

How to Reproduce

On a machine without an NVIDIA driver. I used the ubuntu latest runner on GitHub Actions with Python 3.12.

pip install "cuda-core[cu12]==1.2.1"

from cuda.core import Program, ProgramOptions

src = 'extern "C" __global__ void k(float* x) { x[0] = 2.0f * x[0] + 1.0f; }'

# Works without a driver
Program(src, code_type="c++", options=ProgramOptions(arch="sm_75")).compile("cubin")

# Fails without a driver
Program(src, code_type="c++", options=ProgramOptions(arch="compute_75")).compile("ptx")

A public run on a runner with no libcuda shows both cases, the cubin compile passes and the ptx compile fails. https://github.com/VolodymyrLinuxovich/heat-risk-cuda/actions/runs/37217831804

Trimmed traceback from the failing run

cuda/core/_program.pyx:222: in cuda.core._program.Program.compile
cuda/core/_program.pyx:738: in cuda.core._program._program_compile_uncached
cuda/core/_program.pyx:1192: in cuda.core._program.Program_compile
cuda/core/_program.pyx:815: in cuda.core._program._can_load_generated_ptx
cuda/core/_utils/version.pyx:37: in cuda.core._utils.version.driver_version
cuda/bindings/driver.pyx:23154: in cuda.bindings.driver.cuDriverGetVersion
...
cuda.pathfinder._dynamic_libs.load_dl_common.DynamicLibNotFoundError: "cuda" is an NVIDIA driver library and can only be found via system search. Ensure the NVIDIA display driver is installed.

The _can_load_generated_ptx code on main looks the same as in 1.2.1, so I expect main behaves the same way, but I have only run 1.2.1.

Expected behavior

PTX compilation succeeds without a driver, the same as cubin compilation. When the driver version cannot be determined, the loadability check could skip the warning (or warn that loadability is unknown) instead of failing the compile.

I would be glad to open a PR for this if that approach sounds right to you.

Operating System

Ubuntu (GitHub Actions ubuntu latest runner), no NVIDIA driver

nvidia-smi output

Not available, no driver on that machine.

Dominant language
Cython
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