Building with Clang as host compiler

CUTLASS 3.2(.1) reintroduces support for building with Clang as host compiler, and NVCC as device compiler. This is NOT the same as building with Clang as both host and device compiler (“CUDA Clang”).

Software prerequisites

1. Clang (regularly tested with Clang 17; occasionally tested with Clang 10 and greater)

2. CUDA Toolkit (tested with 12.2; other versions likely work)

3. CMake (at least 3.18)

4. git

5. Python (at least 3.6)

Experience with Ubuntu 22.04 LTS is that clang requires the following packages to be installed.

$ sudo apt-get install clang cmake ninja-build pkg-config libgtk-3-dev liblzma-dev libstdc++-12-dev

A symptom of not installing all needed dependencies is the following error when attempting to use clang: "/usr/bin/ld: cannot find -lstdc++: No such file or directory".

Running CMake

Required CMake options

The Clang build requires specifying the following CMake options. Replace <path-to-clang++> with the path to your clang++ executable. You may use clang++ directly if it is in your PATH.

• CMAKE_CXX_COMPILER=<path-to-clang++>

• CMAKE_CUDA_HOST_COMPILER=<path-to-clang++>

One must set both! It’s not enough just to set the CXX environment variable, for example. Symptoms of only setting CMAKE_CXX_COMPILER (or only setting the CXX environment variable) include cc1plus (GCC’s compiler executable) reporting build errors due to it not understanding Clang’s command-line options.

Users can also specify a particular CUDA Toolkit version by setting the CMake option CMAKE_CUDA_COMPILER to the path to the nvcc executable that lives in the CUDA Toolkit’s directory. For example, if ${PATH_TO_CUDA_TOOLKIT} is the CUDA Toolkit directory, then one can set CMAKE_CUDA_COMPILER as follows.

• CMAKE_CUDA_COMPILER=${PATH_TO_CUDA_TOOLKIT}/bin/nvcc

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