CMake CUDA:与cublas的静态链接

1sbrub3j  于 2023-04-21  发布在  其他
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我想编译CUDALibrarySamples。cuFFT使用cmake,我想编译并链接1d_c2c应用程序与静态版本的cufft库(-lcufft_static)。使用Makefile是微不足道的,我已经添加了-lcufft_static

nvcc -x cu $(FLAGS) $(INC) 1d_c2c_example.cpp -o 1d_c2c_example $(LIBS)

然而,我不确定如何使用cmake来做同样的事情。我注意到cmake有静态标志:CUDA_cublasLt_static_LIBRARYCUDA_cufft_static_LIBRARY等。所以我的问题是我如何才能启用它们?提前谢谢你!
我试过了

target_link_libraries(${ROUTINE}_example PRIVATE ${CUDA_cufft_static_LIBRARY})

但似乎不起作用。
根据@paleonix的建议,我做了以下事情:

target_link_libraries(${ROUTINE}_example PRIVATE CUDA::cufft_static CUDA::cudart).

但我得到以下错误:

/usr/bin/ld: /opt/cuda/lib64/libcufft_static.a(cbdouble_32bit_prime_callback_RT_SM35_plus.o): in function __sti____cudaRegisterAll()': cbdouble_32bit_prime_callback_RT_SM35_plus.compute_86.cudafe1.cpp:(.text.startup+0x1d): undefined reference to __cudaRegisterLinkedBinary_61_cbdouble_32bit_prime_callback_RT_SM35_plus_compute_86_cpp1_ii_dc5d5345

我正在尝试为CUDA库示例构建以下示例:

1d_c2c_example.cpp

#include <complex>
#include <iostream>
#include <random>
#include <vector>    
#include <cuda_runtime.h>
#include <cufftXt.h>
#include "cufft_utils.h"
int main(int argc, char *argv[]) {
    cufftHandle plan;
    cudaStream_t stream = NULL;
    
    int n = 8;
    int batch_size = 2;
    int fft_size = batch_size * n;
    
    using scalar_type = float;
    using data_type = std::complex<scalar_type>;
    std::vector<data_type> data(fft_size);
    for (int i = 0; i < fft_size; i++) {
        data[i] = data_type(i, -i);
    }
    
    std::printf("Input array:\n");
    for (auto &i : data) {
        std::printf("%f + %fj\n", i.real(), i.imag());
    }
    std::printf("=====\n");
    
    cufftComplex *d_data = nullptr;
    
    CUFFT_CALL(cufftCreate(&plan));
    CUFFT_CALL(cufftPlan1d(&plan, data.size(), CUFFT_C2C, batch_size));
    
    CUDA_RT_CALL(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking));
    CUFFT_CALL(cufftSetStream(plan, stream));
    
    // Create device data arrays
    CUDA_RT_CALL(cudaMalloc(reinterpret_cast<void **>(&d_data), sizeof(data_type) * data.size()));
    CUDA_RT_CALL(cudaMemcpyAsync(d_data, data.data(), sizeof(data_type) * data.size(), cudaMemcpyHostToDevice, stream));
    
    CUFFT_CALL(cufftExecC2C(plan, d_data, d_data, CUFFT_FORWARD));
    CUFFT_CALL(cufftExecC2C(plan, d_data, d_data, CUFFT_INVERSE));
    
    CUDA_RT_CALL(cudaMemcpyAsync(data.data(), d_data, sizeof(data_type) * data.size(), cudaMemcpyDeviceToHost, stream));
    
    CUDA_RT_CALL(cudaStreamSynchronize(stream));
    
    /* free resources */
    CUDA_RT_CALL(cudaFree(d_data))
    CUFFT_CALL(cufftDestroy(plan));
    CUDA_RT_CALL(cudaStreamDestroy(stream));
    CUDA_RT_CALL(cudaDeviceReset());
    return EXIT_SUCCESS;
}

CMakeLists.txt

cmake_minimum_required(VERSION 3.18)

set(ROUTINE 1d_c2c)

project(
  "${ROUTINE}_example"
  DESCRIPTION "GPU-Accelerated Fast Fourier Transforms"
  HOMEPAGE_URL "https://docs.nvidia.com/cuda/cufft/index.html"
  LANGUAGES CXX CUDA)

set(CMAKE_CUDA_ARCHITECTURES 80)
find_package(CUDAToolkit REQUIRED)

set(CMAKE_CXX_STANDARD 11)
set(CMAKE_CXX_STANDARD_REQUIRED ON)

if("${CMAKE_BUILD_TYPE}" STREQUAL "")
  set(CMAKE_BUILD_TYPE Release)
endif()

set(CMAKE_CUDA_ARCHITECTURES 80)
#if(CMAKE_CUDA_ARCHITECTURES LESS 60)
    #set(CMAKE_CUDA_ARCHITECTURES 60 70 75 80 86)
    #endif()
set(BUILD_SHARED_LIBS OFF)
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
set(CUFFT_LIBRARIES ${CUDA_cufft_LIBRARY} ${CUDA_culibos_LIBRARY} ${CUDA_cudart_LIBRARY})

add_executable(${ROUTINE}_example)

target_include_directories(${ROUTINE}_example
                           PRIVATE ${CMAKE_CUDA_TOOLKIT_INCLUDE_DIRECTORIES} 
                           ${CMAKE_SOURCE_DIR}/../utils)

target_sources(${ROUTINE}_example
               PRIVATE ${PROJECT_SOURCE_DIR}/${ROUTINE}_example.cpp)

set(CMAKE_CUDA_ARCHITECTURES 80)
#target_link_libraries(${ROUTINE}_example PRIVATE ${CUDA_cufft_static_LIBRARY} CUDA::cufft CUDA::cudart)
target_link_libraries(${ROUTINE}_example PRIVATE CUDA::cufft_static CUDA::cudart)

当我移除

find_package(CUDAToolkit REQUIRED)

cmake显示以下错误:

CMake Error at CMakeLists.txt:82 (target_link_libraries):
   Target "1d_c2c_example" links to:

     CUDA::cufft_static

   but the target was not found.
owfi6suc

owfi6suc1#

在使用CUDA::cufft_static后仍然有链接器问题的主要原因是静态cuFFT需要启用可重定位的设备代码。这在CMake中通过CUDA_SEPARABLE_COMPILATION属性完成。
我将收回我的说法,即不应该同时使用CUDAfind_package(CUDAToolkit REQUIRED)。虽然cufft_static目标在只使用语言时可用,但它不会自动链接culibos。因此更优雅的解决方案似乎是使用包中的CUDA::cufft_static
我从链接库中获取了cufft_utils.h并将其放入${PROJECT_SOURCE_DIR}/utils中。如果您的项目结构不同,则必须调整target_include_directories命令。
设置CMAKE_变量是一种糟糕的方式。为了让其中一些变量正常工作,您必须在project命令之前设置它们。但是,例如,CUDA架构和构建类型应该在第一次配置期间通过命令行参数设置到cmake或使用ccmake来获得一个漂亮的控制台UI。

cmake_minimum_required(VERSION 3.18)

set(ROUTINE 1d_c2c)

project(
  "${ROUTINE}_example"
  DESCRIPTION "GPU-Accelerated Fast Fourier Transforms"
  HOMEPAGE_URL "https://docs.nvidia.com/cuda/cufft/index.html"
  LANGUAGES CXX CUDA)

find_package(CUDAToolkit REQUIRED)

add_executable(${ROUTINE}_example)

set_target_properties(${ROUTINE}_example
  PROPERTIES
    CUDA_SEPARABLE_COMPILATION ON
    RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)

target_compile_features(${ROUTINE}_example
  PRIVATE cuda_std_11)

target_sources(${ROUTINE}_example
  PRIVATE ${PROJECT_SOURCE_DIR}/${ROUTINE}_example.cu)

target_include_directories(${ROUTINE}_example
  PRIVATE ${PROJECT_SOURCE_DIR}/utils)

target_link_libraries(${ROUTINE}_example PRIVATE
  PRIVATE CUDA::cufft_static)

正如你所看到的,我给了源文件一个.cu。让它在.cpp文件中工作似乎有点复杂。阅读cuFFT文档的这一章是一个很好的起点。虽然可以通过使用find_package(Threads REQUIRED)然后将${CMAKE_DL_LIBS}Threads::Threads添加到target_link_libraries命令来消除大多数链接器错误,我无法让可重定位设备代码工作,因为我无法让CMake使用nvcc进行链接。我尝试在set_target_properties中设置LINKER_LANGUAGE CUDA,理论上应该可以工作,但实际上CMake一直使用g++进行链接(在make VERBOSE=1中可见)。这可能是CMake中的一个bug。

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