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Add vLLM-metax vllm metax cmake presets compiler arg #303

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Add vLLM-metax vllm metax cmake presets compiler arg #303

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d046b47
Allow explicit CUDA compiler in CMake presets
ghangz Jun 29, 2026
27f2663
Resolve explicit compiler paths in presets
ghangz Jul 1, 2026
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17 changes: 17 additions & 0 deletions tests/tools/test_generate_cmake_presets.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,17 @@
import json

from tools.generate_cmake_presets import generate_presets


def test_generate_presets_accepts_explicit_cuda_compiler(tmp_path):
output = tmp_path / "CMakeUserPresets.json"

generate_presets(
output_path=str(output),
force_overwrite=True,
cuda_compiler="/opt/maca/bin/cucc",
)

data = json.loads(output.read_text(encoding="utf-8"))
cache = data["configurePresets"][0]["cacheVariables"]
assert cache["CMAKE_CUDA_COMPILER"] == "/opt/maca/bin/cucc"
32 changes: 28 additions & 4 deletions tools/generate_cmake_presets.py
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Expand Up @@ -27,14 +27,21 @@ def get_cpu_cores():
return multiprocessing.cpu_count()


def generate_presets(output_path="CMakeUserPresets.json", force_overwrite=False):
def generate_presets(
output_path="CMakeUserPresets.json",
force_overwrite=False,
cuda_compiler=None,
):
"""Generates the CMakeUserPresets.json file."""

print("Attempting to detect your system configuration...")

# Detect NVCC
nvcc_path = None
if CUDA_HOME:
nvcc_path = cuda_compiler
if nvcc_path:
print(f"Using CUDA-compatible compiler from argument: {nvcc_path}")

@gemini-code-assist gemini-code-assist Bot Jul 1, 2026

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high

If the cuda_compiler argument is provided as a relative path or as a command name, it is written directly to CMakeUserPresets.json without resolution. Since CMake configure presets are executed with the working directory set to the build directory (e.g., ${sourceDir}/cmake-build-release), any relative path will be resolved relative to the build directory rather than the project root, leading to configuration failures. Resolving the compiler path to an absolute path (similar to how python_executable is handled) ensures robust behavior.

    nvcc_path = cuda_compiler
    if nvcc_path:
        if not os.path.isabs(nvcc_path) and which(nvcc_path):
            nvcc_path = os.path.abspath(which(nvcc_path))
        elif not os.path.isabs(nvcc_path):
            nvcc_path = os.path.abspath(nvcc_path)
        print(f"Using CUDA-compatible compiler from argument: {nvcc_path}")


if not nvcc_path and CUDA_HOME:
prospective_path = os.path.join(CUDA_HOME, "bin", "nvcc")
if os.path.exists(prospective_path):
nvcc_path = prospective_path
Expand Down Expand Up @@ -176,6 +183,23 @@ def generate_presets(output_path="CMakeUserPresets.json", force_overwrite=False)
action="store_true",
help="Force overwrite existing CMakeUserPresets.json without prompting",
)
parser.add_argument(
"--output",
default="CMakeUserPresets.json",
help="Output path for the generated presets file",
)
parser.add_argument(
"--cuda-compiler",
help=(
"Path to the CUDA-compatible compiler. Use this in non-interactive "
"MACA containers when the compiler is exposed as cucc/mxcc rather "
"than nvcc."
),
)

args = parser.parse_args()
generate_presets(force_overwrite=args.force_overwrite)
generate_presets(
output_path=args.output,
force_overwrite=args.force_overwrite,
cuda_compiler=args.cuda_compiler,
)