自己怎么来建设网站/市场营销十大经典案例

1， 源代码

仅仅是加入了模板函数和对应的 .cuh文件，当前的目录结构如下：

icmm/gpu/add.cu

#include <stdio.h>
#include <cuda_runtime.h>#include "inc/add.cuh"// different name in this level for different typename, as extern "C" can not decorate template function that is in C++;extern "C"  void  vector_add_gpu_s(float *A, float *B, float *C, int n)
{dim3 grid, block;block.x = 256;grid.x = (n + block.x - 1) / block.x;printf("CUDA kernel launch with %d blocks of %d threads\n", grid.x, block.x);vector_add_kernel<><<<grid, block>>>(A, B, C, n);
}extern "C"  void  vector_add_gpu_d(double* A, double* B, double* C, int n)
{dim3 grid, block;block.x = 256;grid.x = (n + block.x - 1) / block.x;printf("CUDA kernel launch with %d blocks of %d threads\n", grid.x, block.x);vector_add_kernel<><<<grid, block>>>(A, B, C, n);
}

icmm/gpu/add.h

#pragma onceextern "C"  void  vector_add_gpu_s(float *A, float *B, float *C, int n);
extern "C"  void  vector_add_gpu_d(double* A, double* B, double* C, int n);

icmm/gpu/inc/add.cuh

#pragma oncetemplate<typename T>
__global__ void vector_add_kernel(T *A, T *B, T *C, int n)
{int i = blockDim.x * blockIdx.x + threadIdx.x;if (i < n){C[i] = A[i] + B[i] + 0.0f;}
}

icmm/gpu/inc/sub.cuh

#pragma oncetemplate<typename T>
__global__ void vector_sub_kernel(T *A, T *B, T *C, int n)
{int i = blockDim.x * blockIdx.x + threadIdx.x;if (i < n){C[i] = A[i] - B[i] + 0.0f;}
}

icmm/gpu/sub.cu

#include <stdio.h>
#include <cuda_runtime.h>
#include "inc/sub.cuh"extern "C"  void  vector_sub_gpu_s(float *A, float *B, float *C, int n)
{dim3 grid, block;block.x = 256;grid.x = (n + block.x - 1) / block.x;printf("CUDA kernel launch with %d blocks of %d threads\n", grid.x, block.x);vector_sub_kernel<><<<grid, block>>>(A, B, C, n);
}extern "C"  void  vector_sub_gpu_d(double *A, double *B, double *C, int n)
{dim3 grid, block;block.x = 256;grid.x = (n + block.x - 1) / block.x;printf("CUDA kernel launch with %d blocks of %d threads\n", grid.x, block.x);vector_sub_kernel<><<<grid, block>>>(A, B, C, n);
}

icmm/gpu/sub.h

#pragma onceextern "C"  void  vector_sub_gpu_s(float *A, float *B, float *C, int n);
extern "C"  void  vector_sub_gpu_d(double *A, double *B, double *C, int n);

icmm/include/icmm.h

#pragma once
#include<cuda_runtime.h>void hello_print();
void ic_S_add(float* A, float* B, float *C, int n);
void ic_D_add(double* A, double* B, double* C, int n);void ic_S_sub(float* A, float* B, float *C, int n);
void ic_D_sub(float* A, float* B, float *C, int n);

icmm/Makefile

#libicmm.soTARGETS = libicmm.so
GPU_ARCH= -arch=sm_70all: $(TARGETS)sub.o: gpu/sub.cunvcc    -Xcompiler -fPIC $(GPU_ARCH) -c $<add.o: gpu/add.cunvcc    -Xcompiler -fPIC $(GPU_ARCH) -c $<
#-dc
#-rdc=trueadd_link.o: add.onvcc   -Xcompiler -fPIC  $(GPU_ARCH) -dlink   -o $@  $<  -L/usr/local/cuda/lib64 -lcudart -lcudadevrtic_add.o: src/ic_add.cppg++ -fPIC -c $<  -L/usr/local/cuda/lib64 -I/usr/local/cuda/include -lcudart -lcudadevrt -I./ic_sub.o: src/ic_sub.cppg++ -fPIC -c $<  -L/usr/local/cuda/lib64 -I/usr/local/cuda/include -lcudart -lcudadevrt -I./$(TARGETS): sub.o ic_sub.o add.o ic_add.o add_link.omkdir -p libg++ -shared -fPIC  $^  -o lib/libicmm.so -I/usr/local/cuda/include -L/usr/local/cuda/lib64 -lcudart -lcudadevrt -rm -f *.o.PHONY:clean
clean:-rm -f *.o lib/*.so test ./bin/test-rm -rf lib bin

icmm/makefile_bin

# executable
TARGET = test
GPU_ARCH = -arch=sm_70all: $(TARGET)add.o: gpu/add.cunvcc -dc -rdc=true $(GPU_ARCH) -c $<sub.o: gpu/sub.cunvcc -dc -rdc=true $(GPU_ARCH) -c $<add_link.o: add.onvcc $(GPU_ARCH) -dlink   -o $@  $<  -L/usr/local/cuda/lib64 -lcudart -lcudadevrtsub_link.o: sub.onvcc $(GPU_ARCH) -dlink   -o $@  $<  -L/usr/local/cuda/lib64 -lcudart -lcudadevrtic_add.o: src/ic_add.cppg++ -c $<  -L/usr/local/cuda/lib64 -I/usr/local/cuda/include -lcudart -lcudadevrt -I./ic_sub.o: src/ic_sub.cppg++ -c $<  -L/usr/local/cuda/lib64 -I/usr/local/cuda/include -lcudart -lcudadevrt -I./test.o: testing/test.cppg++ -c $< -I/usr/local/cuda/include -L/usr/local/cuda/lib64 -lcudart -lcudadevrt -I./includetest: sub.o ic_sub.o sub_link.o add.o ic_add.o test.o add_link.og++ $^ -L/usr/local/cuda/lib64 -lcudart -lcudadevrt   -o testmkdir ./bincp ./test ./bin/-rm -f *.o.PHONY:clean
clean:-rm -f *.o bin/* $(TARGET)

icmm/src/ic_add.cpp

#include <stdio.h>
#include <cuda_runtime.h>
#include "gpu/add.h"
//extern void vector_add_gpu(float *A, float *B, float *C, int n);void hello_print()
{printf("hello world!\n");
}//void ic_add(float* A, float* B, float *C, int n){  vector_add_gpu(A, B, C, n);}
void ic_S_add(float* A, float* B, float *C, int n)
{vector_add_gpu_s(A, B, C, n);
}void ic_D_add(double* A, double* B, double* C, int n)
{vector_add_gpu_d(A, B, C, n);
}

icmm/src/ic_sub.cpp

#include <stdio.h>
#include <cuda_runtime.h>#include "gpu/sub.h"
//extern void vector_add_gpu(float *A, float *B, float *C, int n);
void ic_S_sub(float* A, float* B, float *C, int n)
{vector_sub_gpu_s(A, B, C, n);
}void ic_D_sub(double* A, double* B, double *C, int n)
{vector_sub_gpu_d(A, B, C, n);
}

icmm/testing/Makefile

#testTARGET = testall: $(TARGET)CXX_FLAGS = -I/usr/local/cuda/include -L/usr/local/cuda/lib64 -lcudart -lcudadevrt  -I../include -L../test.o: test.cppg++  -c $< $(CXX_FLAGS)$(TARGET):test.og++ $< -o $@ -L/usr/local/cuda/lib64 -lcudart -lcudadevrt  -L../lib  -licmm@echo "to execute: export LD_LIBRARY_PATH=${PWD}/../lib".PHONY:clean
clean:-rm -f *.o $(TARGET)

icmm/testing/test.cpp

#include <cuda_runtime.h>
#include <stdio.h>
#include <string.h>
#include <stdlib.h>#include "icmm.h"void add_test_s(float* A, float* B, float* C, int n)
{ic_S_add(A, B, C, n);printf("Copy output data from the CUDA device to the host memory\n");float* h_C = (float*)malloc(n*sizeof(float));cudaMemcpy(h_C, C, n*sizeof(float), cudaMemcpyDeviceToHost);for (int i = 0; i < n; ++i){printf("%3.2f ", h_C[i]);// if (fabs(h_A[i] + h_B[i] - h_C[i]) > 1e-5) {      fprintf(stderr, "Result verification failed at element %d!\n", i);      exit(EXIT_FAILURE);    }}printf("\nTest PASSED\n");free(h_C);
}/**/
void add_test_d(double* A, double* B, double* C, int n)
{ic_D_add(A, B, C, n);printf("Copy output data from the CUDA device to the host memory\n");float *h_C = (float *)malloc(n*sizeof(double));cudaMemcpy(h_C, C, sizeof(double), cudaMemcpyDeviceToHost);for (int i = 0; i < n; ++i){printf("%3.2f ", h_C[i]);// if (fabs(h_A[i] + h_B[i] - h_C[i]) > 1e-5) {      fprintf(stderr, "Result verification failed at element %d!\n", i);      exit(EXIT_FAILURE);    }}printf("\nTest PASSED\n");free(h_C);
}/**/
void sub_test_s(float* A, float* B, float* C, int n)
{ic_S_sub(A, B, C, n);printf("Copy output data from the CUDA device to the host memory\n");float* h_C = (float*)malloc(n*sizeof(float));cudaMemcpy(h_C, C, n*sizeof(float), cudaMemcpyDeviceToHost);for (int i = 0; i < n; ++i){printf("%3.2f ", h_C[i]);// if (fabs(h_A[i] + h_B[i] - h_C[i]) > 1e-5) {      fprintf(stderr, "Result verification failed at element %d!\n", i);      exit(EXIT_FAILURE);    }}printf("\nTest PASSED\n");free(h_C);
}int main(void)
{int n = 50;size_t size = n * sizeof(float);float *h_A = (float *)malloc(size);float *h_B = (float *)malloc(size);float *h_C = (float *)malloc(size);for (int i = 0; i < n; ++i){h_A[i] =  rand() / (float)RAND_MAX;h_B[i] =  rand() / (float)RAND_MAX;}float *d_A = NULL;float *d_B = NULL;float *d_C = NULL;cudaMalloc((void **)&d_A, size);cudaMalloc((void **)&d_B, size);cudaMalloc((void **)&d_C, size);cudaMemcpy(d_A, h_A, size, cudaMemcpyHostToDevice);cudaMemcpy(d_B, h_B, size, cudaMemcpyHostToDevice);
/*int threadsPerBlock = 256;int blocksPerGrid = (n + threadsPerBlock - 1) / threadsPerBlock;printf("CUDA kernel launch with %d blocks of %d threads\n", blocksPerGrid, threadsPerBlock);vector_add_kernel<<<blocksPerGrid, threadsPerBlock>>>(d_A, d_B, d_C, n);
*///ic_add(d_A, d_B, d_C, n);add_test_s(d_A, d_B, d_C, n);sub_test_s(d_A, d_B, d_C, n);cudaFree(d_A);cudaFree(d_B);cudaFree(d_C);free(h_A);free(h_B);free(h_C);printf("Done\n");return 0;
}

2. 总结

.cu 代码给 g++ 的 .cpp 的代码需要使用 extern "C" 来修饰，所以一template 函数的实例化不能一直贯彻到 .cu 源代码的最顶层；