myl7's blog

A little C++ and CUDA with your Rust

Published on 2024-04-12

A little C with your Rust, a well-known article in The Embedded Rust Book, has briefly introduced how to call a C function from Rust without a third-party build dependency. In the post, we will step further to solve the same FFI problem in a more complex scenario: calling a C++ function that additionally contains some CUDA code from Rust without a third-party build dependency, e.g., cxx.

  • Handle name mangling and ensure using the static library
  • Link libstdc++ and libcudart



We discuss the problem on the codebase myl7/fss-prg-cuda. It is a C++ project built with CMake. In the path include, there is a header file as the interface, in which there is C++-only namespace declarations. In the path src, there are definition files that contain CUDA code stored in .cu files. With the CMake configuration, we can build the project to a static .a library and a dynamic .so library. Now, we will add Rust bindings to the project and leverage the Rust test framework to test it.

The API is exported in the header file as:

namespace fssprgcuda {

int Aes128MatyasMeyerOseas(...);

}  // namespace fssprgcuda

The CMake configuration is one of the critical points. We show the initial configuration as below:

# For Ubuntu Jammy 22.04 so far
cmake_minimum_required(VERSION 3.22)
# Set env `CUDACXX=/absolute/path/to/nvcc` to enable the CUDA language
# if nvcc is not in the PATH.
project(fss-prg-cuda LANGUAGES CUDA CXX)

# If the builder is confused by a soft link from /usr/local/cuda-* to /usr/local/cuda,
# pass `-DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-*` to CMake to locate CUDA.

target_compile_features(fssprgcuda PUBLIC cxx_std_17)
set_target_properties(fssprgcuda PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
target_include_directories(fssprgcuda PUBLIC "${CMAKE_CURRENT_SOURCE_DIR}/include")
# The following one line is for a CUDA feature used in this project.
# It does not affect the FFI problem.
target_compile_options(fssprgcuda PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--extended-lambda>)

Notice the flag CUDA_SEPARABLE_COMPILATION. It is suggested in tutorials like this one in the CUDA technical blog

Finally, we start with a primitive Rust binding like:

// src/
pub mod ffi {
    use std::ffi::c_int;

    extern "C" {
        pub fn Aes128MatyasMeyerOseas(...);

The build script of the Rust project is:

fn main() {
    println!("cargo:rustc-link-search={}", "build");

    println!("cargo:rustc-link-lib=static={}", "fssprgcuda");
    println!("cargo:rerun-if-changed={}", "build/libfssprgcuda.a");

Name mangling

When running the build, it should not be surprising to see an unknown symbol error from the linker:

undefined reference to `Aes128MatyasMeyerOseas'
collect2: error: ld returned 1 exit status

Even without the namespace declaration, C++ does name mangling to allow function declaration with the same name but different signatures, which renames the function symbols in the object files and libraries. It is also mentioned in the documentation of the cc crate, an officially recommended tool maintained under the official rust-lang organization.

You can check the mangled name of the current code with the command nm:

$ nm build/libfssprgcuda.a | grep Aes128MatyasMeyerOseas
0000000000000000 T _ZN10fssprgcuda22Aes128MatyasMeyerOseasEPhmPKhm

It is possible to turn off name mangling in C++ for some functions. It is to wrap the function declarations with a extern "C" {} block. (The definitions do not need to be wrapped.) After that, you can get a Aes128MatyasMeyerOseas symbol even though the function is still in a namespace.

An alternative solution is directly using the mangled name in the Rust code. Instead of declaring fn _ZN10fssprgcuda22Aes128MatyasMeyerOseasEPhmPKhm, you can use the #[link_name] attribute to use an alias name in the Rust code:

// src/
#[link_name = "_ZN10fssprgcuda22Aes128MatyasMeyerOseasEPhmPKhm"]
pub fn aes128_matyas_meyer_oseas(...);

We will choose the latter because we do not need to modify the library API or add some C++ wrapper code.

Here, notice the static={} segment. Suppose you omit the explicit library type declaration. In that case, the linker will choose the dynamic library by default, documented even in the The rustc book other than the Build Scripts page of The Cargo Book. Because the build directory is not in the dynamic library searching path in runtime, Cargo would always report unknown symbol errors for the exported API. In contrast, the API symbol is correctly exported. You can see it with the nm command.


Rerun the build, and now we get many errors taking up the screen. (C++ style, isn’t it?) We can see the following lines in all the errors:

/usr/bin/ld: fssprgcuda.cpp:(.text+0x8a): undefined reference to `std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >::~basic_string()'
/usr/bin/ld: fssprgcuda.cpp:(.text+0x93): undefined reference to `std::allocator<char>::~allocator()'

Which says the linker can not find the implementation of <string> of the C++ standard library.

The point is that besides only including libc, C++ also links libraries like libstdc++ to provide some implementations of the standard library, like <string>. Another example that should be more familiar is <thread>, which requires linking with pthread to get the implementation. The requirement is also mentioned in the documentation of the cc crate.

To fix some of the unknown symbol errors, add the following line to the build script to link, e.g., libstdc++:

println!("cargo:rustc-link-lib=dylib={}", "stdc++");

Staticly linking with libstdc++ by replacing dylib with static should also work. But Cargo can not find a static libstdc++ on my system, so I have not tested it. If dynamically linking, you must put the above line after the println!("cargo:rustc-link-lib=static={}", "fssprgcuda"); line to make the symbols found.

cudart: CUDA runtime API

Now, the error number has decreased a lot, but we still get unknown symbol errors like:

/usr/local/cuda-12.1/bin/../targets/x86_64-linux/include/crt/host_runtime.h:259: undefined reference to `__cudaUnregisterFatBinary'
/usr/bin/ld: build/libfssprgcuda.a( in function `__nv_init_managed_rt_with_module(void**)':
/usr/local/cuda-12.1/bin/../targets/x86_64-linux/include/crt/host_runtime.h:264: undefined reference to `__cudaInitModule'

They are from the CUDA runtime API library libcudart and are required in runtime, which we can also infer from the names, e.g., __cudaUnregisterFatBinary. Like libstdc++, we need to add the following line to the build script to link it and ensure it is after the fssprgcuda line:

println!("cargo:rustc-link-lib=dylib={}", "cudart");

You may also want to add the line println!("cargo:rustc-link-search={}", "/usr/local/cuda/lib64"); if Cargo can not find the CUDA library by default.

Some answers, e.g., this one to the question about the undefined reference to __cudaRegisterLinkedBinary suggest one more library, cudadevrt, which should be about development-purpose runtime API inferred from the name. However, this project does not require it.

The final barrier is some weird unknown symbol errors:

/usr/bin/ld: build/libfssprgcuda.a( in function `__sti____cudaRegisterAll()':
/tmp/tmpxft_00005164_00000000-6_kernels.cudafe1.stub.c:21: undefined reference to `__cudaRegisterLinkedBinary_ff2660a9_10_kernels_cu_9b2baf5b_20846'
/usr/bin/ld: build/libfssprgcuda.a( in function `__sti____cudaRegisterAll()':
/tmp/tmpxft_00001725_00000000-6_owcf.cudafe1.stub.c:14: undefined reference to `__cudaRegisterLinkedBinary_aa40f2b2_7_owcf_cu_617d277f'
/usr/bin/ld: build/libfssprgcuda.a( in function `__sti____cudaRegisterAll()':
/tmp/tmpxft_00001726_00000000-6_aes.cudafe1.stub.c:14: undefined reference to `__cudaRegisterLinkedBinary_fa6d3751_6_aes_cu_96e0c4dd'
collect2: error: ld returned 1 exit status

We can see _kernels_cu_, _owcf_cu_, and _aes_cu_ in the symbol names, meaning the symbols are related to our source files.

The solution is available in this GitHub gist about the CUDA link error with CMake. CUDA generates some glue code as object files in the path build/CMakeFiles/fssprgcuda.dir linked during device linking. Usually, the compiler (nvcc mostly) defers device linking until generating a shared library or executable. In this project, CMake leaves the device linking to Cargo, and Cargo can not do that. You can find more in the documentation of CUDA_RESOLVE_DEVICE_SYMBOLS of CMake.

To solve it, we do device linking in CMake by setting the following line in the CMake configuration together with the flag CUDA_SEPARABLE_COMPILATION:

  fssprgcuda PROPERTIES

Now everything works fine. 🎉!