Luke Granger-Brown
57725ef3ec
git-subtree-dir: third_party/nixpkgs git-subtree-split: 76612b17c0ce71689921ca12d9ffdc9c23ce40b2
97 lines
4.8 KiB
Markdown
97 lines
4.8 KiB
Markdown
# Cuda modules
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> [!NOTE]
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> This document is meant to help CUDA maintainers understand the structure of
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> the CUDA packages in Nixpkgs. It is not meant to be a user-facing document.
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> For a user-facing document, see [the CUDA section of the manual](../../../doc/languages-frameworks/cuda.section.md).
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The files in this directory are added (in some way) to the `cudaPackages`
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package set by [cuda-packages.nix](../../top-level/cuda-packages.nix).
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## Top-level files
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Top-level nix files are included in the initial creation of the `cudaPackages`
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scope. These are typically required for the creation of the finalized
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`cudaPackages` scope:
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- `backend-stdenv.nix`: Standard environment for CUDA packages.
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- `flags.nix`: Flags set, or consumed by, NVCC in order to build packages.
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- `gpus.nix`: A list of supported NVIDIA GPUs.
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- `nvcc-compatibilities.nix`: NVCC releases and the version range of GCC/Clang
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they support.
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## Top-level directories
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- `cuda`: CUDA redistributables! Provides extension to `cudaPackages` scope.
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- `cudatoolkit`: monolithic CUDA Toolkit run-file installer. Provides extension
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to `cudaPackages` scope.
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- `cudnn`: NVIDIA cuDNN library.
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- `cutensor`: NVIDIA cuTENSOR library.
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- `generic-builders`:
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- Contains a builder `manifest.nix` which operates on the `Manifest` type
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defined in `modules/generic/manifests`. Most packages are built using this
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builder.
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- Contains a builder `multiplex.nix` which leverages the Manifest builder. In
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short, the Multiplex builder adds multiple versions of a single package to
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single instance of the CUDA Packages package set. It is used primarily for
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packages like `cudnn` and `cutensor`.
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- `modules`: Nixpkgs modules to check the shape and content of CUDA
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redistributable and feature manifests. These modules additionally use shims
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provided by some CUDA packages to allow them to re-use the
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`genericManifestBuilder`, even if they don't have manifest files of their
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own. `cudnn` and `tensorrt` are examples of packages which provide such
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shims. These modules are further described in the
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[Modules](./modules/README.md) documentation.
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- `nccl`: NVIDIA NCCL library.
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- `nccl-tests`: NVIDIA NCCL tests.
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- `saxpy`: Example CMake project that uses CUDA.
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- `setup-hooks`: Nixpkgs setup hooks for CUDA.
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- `tensorrt`: NVIDIA TensorRT library.
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## Distinguished packages
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### Cuda compatibility
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[Cuda Compatibility](https://docs.nvidia.com/deploy/cuda-compatibility/),
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available as `cudaPackages.cuda_compat`, is a component which makes it possible
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to run applications built against a newer CUDA toolkit (for example CUDA 12) on
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a machine with an older CUDA driver (for example CUDA 11), which isn't possible
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out of the box. At the time of writing, Cuda Compatibility is only available on
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the Nvidia Jetson architecture, but Nvidia might release support for more
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architectures in the future.
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As Cuda Compatibility strictly increases the range of supported applications, we
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try our best to enable it by default on supported platforms.
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#### Functioning
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`cuda_compat` simply provides a new `libcuda.so` (and associated variants) that
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needs to be used in place of the default CUDA driver's `libcuda.so`. However,
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the other shared libraries of the default driver must still be accessible:
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`cuda_compat` isn't a complete drop-in replacement for the driver (and that's
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the point, otherwise, it would just be a newer driver).
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Nvidia's recommendation is to set `LD_LIBRARY_PATH` to points to `cuda_compat`'s
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driver. This is fine for a manual, one-shot usage, but in general setting
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`LD_LIBRARY_PATH` is a red flag. This is global state which short-circuits most
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of other dynamic libraries resolution mechanisms and can break things in
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non-obvious ways, especially with other Nix-built software.
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#### Cuda compat with Nix
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Since `cuda_compat` is a known derivation, the easy way to do this in Nix would
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be to add `cuda_compat` as a dependency of CUDA libraries and applications and
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let Nix does its magic by filling the `DT_RUNPATH` fields. However,
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`cuda_compat` itself depends on `libnvrm_mem` and `libnvrm_gpu` which are loaded
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dynamically at runtime from `/run/opengl-driver`. This doesn't please the Nix
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sandbox when building, which can't find those (a second minor issue is that
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`addOpenGLRunpathHook` prepends the `/run/opengl-driver` path, so that would
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still take precedence).
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The current solution is to do something similar to `addOpenGLRunpathHook`: the
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`addCudaCompatRunpathHook` prepends to the path to `cuda_compat`'s `libcuda.so`
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to the `DT_RUNPATH` of whichever package includes the hook as a dependency, and
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we include the hook by default for packages in `cudaPackages` (by adding it as a
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inputs in `genericManifestBuilder`). We also make sure it's included after
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`addOpenGLRunpathHook`, so that it appears _before_ in the `DT_RUNPATH` and
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takes precedence.
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