53 lines
2.1 KiB
Markdown
53 lines
2.1 KiB
Markdown
# CUDA {#cuda}
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CUDA-only packages are stored in the `cudaPackages` packages set. This set
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includes the `cudatoolkit`, portions of the toolkit in separate derivations,
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`cudnn`, `cutensor` and `nccl`.
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A package set is available for each CUDA version, so for example
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`cudaPackages_11_6`. Within each set is a matching version of the above listed
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packages. Additionally, other versions of the packages that are packaged and
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compatible are available as well. For example, there can be a
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`cudaPackages.cudnn_8_3_2` package.
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To use one or more CUDA packages in an expression, give the expression a `cudaPackages` parameter, and in case CUDA is optional
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```nix
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cudaSupport ? false
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cudaPackages ? {}
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```
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When using `callPackage`, you can choose to pass in a different variant, e.g.
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when a different version of the toolkit suffices
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```nix
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mypkg = callPackage { cudaPackages = cudaPackages_11_5; }
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```
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If another version of say `cudnn` or `cutensor` is needed, you can override the
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package set to make it the default. This guarantees you get a consistent package
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set.
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```nix
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mypkg = let
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cudaPackages = cudaPackages_11_5.overrideScope' (final: prev {
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cudnn = prev.cudnn_8_3_2;
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}});
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in callPackage { inherit cudaPackages; };
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```
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The CUDA NVCC compiler requires flags to determine which hardware you
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want to target for in terms of SASS (real hardware) or PTX (JIT kernels).
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Nixpkgs tries to target support real architecture defaults based on the
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CUDA toolkit version with PTX support for future hardware. Experienced
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users may optimize this configuration for a variety of reasons such as
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reducing binary size and compile time, supporting legacy hardware, or
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optimizing for specific hardware.
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You may provide capabilities to add support or reduce binary size through
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`config` using `cudaCapabilities = [ "6.0" "7.0" ];` and
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`cudaForwardCompat = true;` if you want PTX support for future hardware.
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Please consult [GPUs supported](https://en.wikipedia.org/wiki/CUDA#GPUs_supported)
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for your specific card(s).
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Library maintainers should consult [NVCC Docs](https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/)
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and release notes for their software package.
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