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MAC에서 QT + CUDA 사용하기 본문

[ 프로그래밍 ]

MAC에서 QT + CUDA 사용하기

K. Martin 2014.07.17 04:12

1. 준비사항

∙ CUDA 사용이 가능한 GPU (CUDA 사용 가능 하드웨어 목록)

 Mac OS X 10.8 or later 

 gcc 또는 Clang 컴파일러와 툴체인이 Xcode에 설치되어 있을 것

 Command Line Tools 패키지 설치 필요

 the NVIDIA CUDA Toolkit 설치할 것(CUDA Download page)

 환경변수 설정 (매우 중요)

    export PATH=/Developer/NVIDIA/CUDA-6.0/bin:$PATH 

    export DYLD_LIBRARY_PATH=/Developer/NVIDIA/CUDA-6.0/lib:$DYLD_LIBRARY_PATH


2. 설치 확인

∙ 드라이버 설치 확인

kextstat | grep -i cuda

∙ 컴파일러 설치 확인

nvcc -V

∙ 예제프로그램 컴파일 후 실행

make -C 1_Utilities/deviceQuery

cd bin/x86_64/darwin/release

./deviceQuery



3. *QT Creator에서 설정하기

∙ .pro (맨 아래 네 줄이 가장 중요한 포인트임)


QT       += core
QT       -= gui

TARGET = cudatest    # depending on the project


CONFIG   += console
CONFIG   -= app_bundle

TEMPLATE = app

# Basic .pro configuration
SOURCES += \
    main.cpp

# This makes the .cu files appear in your project
OTHER_FILES += main.cu

# Cuda sources
CUDA_SOURCES += main.cu

# CUDA settings (depending on the system)
CUDA_DIR = /usr/local/cuda      # Path to cuda toolkit install

# nvcc flags (ptxas option verbose is always useful)
NVCCFLAGS = --compiler-options -fno-strict-aliasing -use_fast_math --ptxas-options=-v

# include paths
INCLUDEPATH += $$CUDA_DIR/include

# lib dirs
QMAKE_LIBDIR += $$CUDA_DIR/lib

# libs
LIBS += -lcudart

# join the includes in a line
CUDA_INC = $$join(INCLUDEPATH,' -I','-I',' ')

# Prepare the extra compiler configuration
cuda.input = CUDA_SOURCES
cuda.output = ${OBJECTS_DIR}${QMAKE_FILE_BASE}_cuda.o
cuda.commands = $$CUDA_DIR/bin/nvcc -gencode arch=compute_10,code=sm_10 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_32,code=sm_32 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_50,code=compute_50 -c $$NVCCFLAGS $$CUDA_INC $$LIBS ${QMAKE_FILE_NAME} -o ${QMAKE_FILE_OUT}
cuda.dependency_type = TYPE_C
cuda.depend_command = $$CUDA_DIR/bin/nvcc -gencode arch=compute_10,code=sm_10 -gencode arch=compute_20,code=sm_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_32,code=sm_32 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_50,code=compute_50 $$CUDA_INC $$NVCCFLAGS ${QMAKE_FILE_NAME}

# Tell Qt that we want add more stuff to the Makefile
QMAKE_EXTRA_COMPILERS += cuda
QMAKE_MACOSX_DEPLOYMENT_TARGET = 10.9
QMAKE_CXXFLAGS += -stdlib=libstdc++

QMAKE_LFLAGS += -stdlib=libstdc++ -rpath $$CUDA_DIR/lib


∙ main.cpp

#include <QtCore/QCoreApplication>
#include <cuda.h>

using namespace std;

void run();

int main(int argc, char *argv[])
{
    QCoreApplication a(argc, argv);

    run();

    return a.exec();
}


∙ main.cu

#include <iostream>
#include <string>

#include "cuda_runtime.h"
#include "device_launch_parameters.h"

#define SIZE 1024

using namespace std;

__global__ void VectorAdd(int *a, int *b, int *c, int n)
{
    int i = threadIdx.x;

    if( i < n )
        c[i] = a[i] + b[i];
}

void run()
{
    int *a, *b, *c;
    int *d_a, *d_b, *d_c;

    a = (int *)malloc( SIZE * sizeof(int) );
    b = (int *)malloc( SIZE * sizeof(int) );
    c = (int *)malloc( SIZE * sizeof(int) );

    cudaMalloc( &d_a, SIZE * sizeof(int) );
    cudaMalloc( &d_b, SIZE * sizeof(int) );
    cudaMalloc( &d_c, SIZE * sizeof(int) );

    int i;
    for( i=0; i<SIZE; ++i )
    {
        a[i] = i;
        b[i] = i;
        c[i] = 0;
    }

    cudaMemcpy( d_a, a, SIZE * sizeof(int), cudaMemcpyHostToDevice );
    cudaMemcpy( d_b, b, SIZE * sizeof(int), cudaMemcpyHostToDevice );
    cudaMemcpy( d_c, c, SIZE * sizeof(int), cudaMemcpyHostToDevice );

//    VectorAdd( a, b, c, SIZE );
    VectorAdd<<< 1, SIZE >>>(d_a, d_b, d_c, SIZE);

    cudaMemcpy( a, d_a, SIZE * sizeof(int), cudaMemcpyDeviceToHost );
    cudaMemcpy( b, d_b, SIZE * sizeof(int), cudaMemcpyDeviceToHost );
    cudaMemcpy( c, d_c, SIZE * sizeof(int), cudaMemcpyDeviceToHost );

    for( i=0; i<10; ++i )
        printf( "c[%d] = %d\n", i, c[i] );

    free(a);
    free(b);
    free(c);

    cudaFree(d_a);
    cudaFree(d_b);
    cudaFree(d_c);
}



4. 테스트 결과





SPECIAL THANKS TO 문상환

출처 : http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-mac-os-x


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