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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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評估

難度
2/5
預估耗時
1-3 小時
新手友好度
70/100
Issue 類型
缺陷
描述清晰度
描述清楚
活躍度
活躍
技術堆疊
python
領域
compilers

研究方向

從 cuda/core/_program.pyx 中的 _can_load_generated_ptx()(約第 815 行)和 Program.compile 的 cache-hit 分支(約第 1192 行)開始;引發異常的呼叫是 cuda/core/_utils/version.pyx 中的 driver_version(),它需要 libcuda。捕獲 DynamicLibNotFoundError 並跳過可載入性警告而不是失敗,模仿 cubin 路徑。在無驅動程式的機器上使用程式碼片段重現,並檢查現有的 cuda.core 程式測試;完成意味著 PTX 在沒有驅動程式的情況下編譯,並且警告(或靜默跳過)取代錯誤。

由索引模型根據 Issue 內容生成。

描述

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.

主要語言
Cython
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3.4k
分支
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平均合併
1 天 18 小時
30 天內合併 PR
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