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Corrections for python/README.md (#401)

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Document that published `cuda-bench` wheels are multi-CUDA
wheels containing both CUDA 12.x and CUDA 13.x native extensions,
with runtime selection driven by the installed cuda.bindings major
version.

Clarify that the cu12/cu13 extras select compatible cuda-bindings
dependency families rather than different cuda-bench wheels.

Update source-build instructions to use CUDAARCHS=all-major, avoid
editable installs while the versioned extension layout is unsupported
there, and note that local builds only produce the extension for the
Toolkit found by CMake.

closes #391
This commit is contained in:
Oleksandr Pavlyk
2026-07-01 14:05:31 -05:00
committed by GitHub
parent 21f23decc4
commit e0198df47f
2 changed files with 55 additions and 15 deletions
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58
python/README.md
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@@ -5,43 +5,79 @@ Library `NVBench`.
## Installation
Install from PyPi
Install from PyPI:
```bash
pip install cuda-bench[cu13] # For CUDA 13.x
pip install cuda-bench[cu12] # For CUDA 12.x
python -m pip install cuda-bench
```
Use an optional dependency if you want `pip` to install a compatible
`cuda-bindings` package as well:
```bash
python -m pip install "cuda-bench[cu12]" # Install cuda-bindings 12.x
python -m pip install "cuda-bench[cu13]" # Install cuda-bindings 13.x
```
The published Linux wheel is compatible with both CUDA 12.x and CUDA 13.x
Python environments. It contains two native extensions: one built with a CUDA
12.x Toolkit and installed under `cuda.bench.cu12`, and one built with a CUDA
13.x Toolkit and installed under `cuda.bench.cu13`. At runtime, `cuda-bench`
queries the installed `cuda.bindings` package to determine the CUDA major
version and loads the matching native extension.
The `cu12` and `cu13` extras do not select different `cuda-bench` wheels. They
only select the compatible `cuda-bindings` dependency family. If your
environment already provides an appropriate `cuda-bindings` 12.x or 13.x
package, installing plain `cuda-bench` is sufficient.
A local CUDA Toolkit is not required when installing a published wheel, but the
NVIDIA driver must support the CUDA runtime used by the installed
`cuda.bindings` package. Use the same CUDA major version for other CUDA Python
binary packages in the environment, for example `cupy-cuda12x` with
`cuda-bench[cu12]` or `cupy-cuda13x` with `cuda-bench[cu13]`.
## Building from source
### Ensure recent version of CMake
Since `nvbench` requires a rather new version of CMake (>=3.30.4), either build CMake from sources, or create a conda environment with a recent version of CMake, using
Since `nvbench` requires CMake >=3.30.4, either install a recent CMake or
create a conda environment with CMake and Ninja:
```
conda create -n build_env --yes cmake ninja
```bash
conda create -n build_env --yes cmake ninja
conda activate build_env
```
### Ensure CUDA compiler
Since building `NVBench` library requires CUDA compiler, ensure that appropriate environment variables
are set. For example, assuming CUDA toolkit is installed system-wide, and assuming Ampere GPU architecture:
Building `cuda-bench` from source requires a CUDA Toolkit with `nvcc`. Ensure
that the appropriate environment variables are set. For example, on Linux,
assuming the CUDA Toolkit is installed system-wide:
```bash
export CUDACXX=/usr/local/cuda/bin/nvcc
export CUDAARCHS=86
export CUDAARCHS=all-major
```
Unlike the published wheel, a local source build only builds the native
extension for the CUDA Toolkit found by CMake. The CUDA major version selected
in the install command below must match that Toolkit.
### Build Python project
Now switch to python folder, configure and install NVBench library, and install the package in editable mode:
Now switch to the Python package directory and install `cuda-bench` from source:
```bash
cd nvbench/python
pip install -e .
python -m pip install ".[cu12]" # If CUDACXX points to a CUDA 12.x toolkit
python -m pip install ".[cu13]" # If CUDACXX points to a CUDA 13.x toolkit
```
Editable installs (`python -m pip install -e .`) are currently not supported.
They do not install the versioned CUDA extension layout used by `cuda-bench`.
Re-run the non-editable install command after making source changes.
### Verify that package works
```bash

12
python/pyproject.toml
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@@ -7,7 +7,7 @@ build-backend = "scikit_build_core.build"
[project]
name = "cuda-bench"
description = "CUDA Kernel Benchmarking Package"
description = "CUDA Kernel Benchmarking Package with CUDA 12.x and 13.x runtime support"
authors = [{ name = "NVIDIA Corporation" }]
license = { text = "Apache-2.0 WITH LLVM-exception" }
classifiers = [
@@ -28,10 +28,14 @@ dynamic = ["version"]
readme = { file = "README.md", content-type = "text/markdown" }
[project.optional-dependencies]
# CUDA 12.x dependencies
# The published wheel is intentionally multi-CUDA: CI builds one CUDA 12.x
# native extension and one CUDA 13.x native extension, then merges both into one
# wheel under cuda/bench/cu12 and cuda/bench/cu13.
#
# These extras do not select different cuda-bench wheels. They select the
# cuda-bindings major version used at runtime to choose the matching native
# extension.
cu12 = ["cuda-bindings>=12.0.0,<13.0.0"]
# CUDA 13.x dependencies
cu13 = ["cuda-bindings>=13.0.0,<14.0.0"]
# Test dependencies for CUDA 12