1.矢量求和

1.1 CPU


#include <stdio.h>#define N   10void add( int *a, int *b, int *c ) {int tid = 0;    // this is CPU zero, so we start at zerowhile (tid < N) {c[tid] = a[tid] + b[tid];tid += 1;   // we have one CPU, so we increment by one}
}int main( void ) {int a[N], b[N], c[N];// fill the arrays 'a' and 'b' on the CPUfor (int i=0; i<N; i++) {a[i] = -i;b[i] = i * i;}add( a, b, c );// display the resultsfor (int i=0; i<N; i++) {printf( "%d + %d = %d\n", a[i], b[i], c[i] );}return 0;
}

输出：

1.2 GPU


#include <stdio.h>#define N   10__global__ void add( int *a, int *b, int *c ) {int tid = blockIdx.x;    // this thread handles the data at its thread idif (tid < N)c[tid] = a[tid] + b[tid];
}int main( void ) {int a[N], b[N], c[N];int *dev_a, *dev_b, *dev_c;// allocate the memory on the GPUcudaMalloc( (void**)&dev_a, N * sizeof(int) ) ;cudaMalloc( (void**)&dev_b, N * sizeof(int) ) ;cudaMalloc( (void**)&dev_c, N * sizeof(int) ) ;// fill the arrays 'a' and 'b' on the CPUfor (int i=0; i<N; i++) {a[i] = -i;b[i] = i * i;}// copy the arrays 'a' and 'b' to the GPUcudaMemcpy( dev_a, a, N * sizeof(int),cudaMemcpyHostToDevice  );cudaMemcpy( dev_b, b, N * sizeof(int),cudaMemcpyHostToDevice  );add<<<N,1>>>( dev_a, dev_b, dev_c );// copy the array 'c' back from the GPU to the CPUcudaMemcpy( c, dev_c, N * sizeof(int),cudaMemcpyDeviceToHost  );// display the resultsfor (int i=0; i<N; i++) {printf( "%d + %d = %d\n", a[i], b[i], c[i] );}// free the memory allocated on the GPUcudaFree( dev_a ) ;cudaFree( dev_b ) ;cudaFree( dev_c ) ;return 0;
}

1.3 GPU （数据大）


#include <stdio.h>#define N   (32 * 1024)__global__ void add( int *a, int *b, int *c ) {int tid = blockIdx.x;while (tid < N) {c[tid] = a[tid] + b[tid];tid += gridDim.x;}
}int main( void ) {int *a, *b, *c;int *dev_a, *dev_b, *dev_c;// allocate the memory on the CPUa = (int*)malloc( N * sizeof(int) );b = (int*)malloc( N * sizeof(int) );c = (int*)malloc( N * sizeof(int) );// allocate the memory on the GPUcudaMalloc( (void**)&dev_a, N * sizeof(int) ) ;cudaMalloc( (void**)&dev_b, N * sizeof(int) ) ;cudaMalloc( (void**)&dev_c, N * sizeof(int) ) ;// fill the arrays 'a' and 'b' on the CPUfor (int i=0; i<N; i++) {a[i] = i;b[i] = 2 * i;}// copy the arrays 'a' and 'b' to the GPUcudaMemcpy( dev_a, a, N * sizeof(int),cudaMemcpyHostToDevice ) ;cudaMemcpy( dev_b, b, N * sizeof(int),cudaMemcpyHostToDevice ) ;add<<<128,1>>>( dev_a, dev_b, dev_c );// copy the array 'c' back from the GPU to the CPUcudaMemcpy( c, dev_c, N * sizeof(int),cudaMemcpyDeviceToHost ) ;// verify that the GPU did the work we requestedbool success = true;for (int i=0; i<N; i++) {if ((a[i] + b[i]) != c[i]) {printf( "Error:  %d + %d != %d\n", a[i], b[i], c[i] );success = false;}}if (success)    printf( "We did it!\n" );// free the memory we allocated on the GPUcudaFree( dev_a ) ;cudaFree( dev_b ) ;cudaFree( dev_c ) ;// free the memory we allocated on the CPUfree( a );free( b );free( c );return 0;
}

2. Julia集曲线

2.1 CPU


#include <GL/glut.h>#define DIM 1000
struct CPUBitmap {unsigned char    *pixels;int     x, y;void    *dataBlock;void (*bitmapExit)(void*);CPUBitmap( int width, int height, void *d = NULL ) {pixels = new unsigned char[width * height * 4];x = width;y = height;dataBlock = d;}~CPUBitmap() {delete [] pixels;}unsigned char* get_ptr( void ) const   { return pixels; }long image_size( void ) const { return x * y * 4; }void display_and_exit( void(*e)(void*) = NULL ) {CPUBitmap**   bitmap = get_bitmap_ptr();*bitmap = this;bitmapExit = e;// a bug in the Windows GLUT implementation prevents us from// passing zero arguments to glutInit()int c=1;char* dummy = "";glutInit( &c, &dummy );glutInitDisplayMode( GLUT_SINGLE | GLUT_RGBA );glutInitWindowSize( x, y );glutCreateWindow( "bitmap" );glutKeyboardFunc(Key);glutDisplayFunc(Draw);glutMainLoop();}// static method used for glut callbacksstatic CPUBitmap** get_bitmap_ptr( void ) {static CPUBitmap   *gBitmap;return &gBitmap;}// static method used for glut callbacksstatic void Key(unsigned char key, int x, int y) {switch (key) {case 27:CPUBitmap*   bitmap = *(get_bitmap_ptr());if (bitmap->dataBlock != NULL && bitmap->bitmapExit != NULL)bitmap->bitmapExit( bitmap->dataBlock );exit(0);}}// static method used for glut callbacksstatic void Draw( void ) {CPUBitmap*   bitmap = *(get_bitmap_ptr());glClearColor( 0.0, 0.0, 0.0, 1.0 );glClear( GL_COLOR_BUFFER_BIT );glDrawPixels( bitmap->x, bitmap->y, GL_RGBA, GL_UNSIGNED_BYTE, bitmap->pixels );glFlush();}
};struct cuComplex {float   r;float   i;cuComplex( float a, float b ) : r(a), i(b)  {}float magnitude2( void ) { return r * r + i * i; }cuComplex operator*(const cuComplex& a) {return cuComplex(r*a.r - i*a.i, i*a.r + r*a.i);}cuComplex operator+(const cuComplex& a) {return cuComplex(r+a.r, i+a.i);}
};int julia( int x, int y ) { const float scale = 1.5;float jx = scale * (float)(DIM/2 - x)/(DIM/2);float jy = scale * (float)(DIM/2 - y)/(DIM/2);cuComplex c(-0.8, 0.156);cuComplex a(jx, jy);int i = 0;for (i=0; i<200; i++) {a = a * a + c;if (a.magnitude2() > 1000)return 0;}return 1;
}void kernel( unsigned char *ptr ){for (int y=0; y<DIM; y++) {for (int x=0; x<DIM; x++) {int offset = x + y * DIM;int juliaValue = julia( x, y );ptr[offset*4 + 0] = 255 * juliaValue;ptr[offset*4 + 1] = 0;ptr[offset*4 + 2] = 0;ptr[offset*4 + 3] = 255;}}}int main( void ) {CPUBitmap bitmap( DIM, DIM );unsigned char *ptr = bitmap.get_ptr();kernel( ptr );bitmap.display_and_exit();
}

编译，运行：

2.2 GPU

// nvcc julia_gpu.cu -o julia -lglut -lcuda#include <GL/glut.h>#ifndef DIM
#define DIM 1000
#endif
struct CPUBitmap {unsigned char    *pixels;int     x, y;void    *dataBlock;void (*bitmapExit)(void*);CPUBitmap( int width, int height, void *d = NULL ) {pixels = new unsigned char[width * height * 4];x = width;y = height;dataBlock = d;}~CPUBitmap() {delete [] pixels;}unsigned char* get_ptr( void ) const   { return pixels; }long image_size( void ) const { return x * y * 4; }void display_and_exit( void(*e)(void*) = NULL ) {CPUBitmap**   bitmap = get_bitmap_ptr();*bitmap = this;bitmapExit = e;// a bug in the Windows GLUT implementation prevents us from// passing zero arguments to glutInit()int c=1;char* dummy = "";glutInit( &c, &dummy );glutInitDisplayMode( GLUT_SINGLE | GLUT_RGBA );glutInitWindowSize( x, y );glutCreateWindow( "bitmap" );glutKeyboardFunc(Key);glutDisplayFunc(Draw);glutMainLoop();}// static method used for glut callbacksstatic CPUBitmap** get_bitmap_ptr( void ) {static CPUBitmap   *gBitmap;return &gBitmap;}// static method used for glut callbacksstatic void Key(unsigned char key, int x, int y) {switch (key) {case 27:CPUBitmap*   bitmap = *(get_bitmap_ptr());if (bitmap->dataBlock != NULL && bitmap->bitmapExit != NULL)bitmap->bitmapExit( bitmap->dataBlock );exit(0);}}// static method used for glut callbacksstatic void Draw( void ) {CPUBitmap*   bitmap = *(get_bitmap_ptr());glClearColor( 0.0, 0.0, 0.0, 1.0 );glClear( GL_COLOR_BUFFER_BIT );glDrawPixels( bitmap->x, bitmap->y, GL_RGBA, GL_UNSIGNED_BYTE, bitmap->pixels );glFlush();}
};struct cuComplex {float   r;float   i;__device__ cuComplex( float a, float b ) : r(a), i(b)  {}__device__ float magnitude2( void ) {return r * r + i * i;}__device__ cuComplex operator*(const cuComplex& a) {return cuComplex(r*a.r - i*a.i, i*a.r + r*a.i);}__device__ cuComplex operator+(const cuComplex& a) {return cuComplex(r+a.r, i+a.i);}
};__device__ int julia( int x, int y ) {const float scale = 1.5;float jx = scale * (float)(DIM/2 - x)/(DIM/2);float jy = scale * (float)(DIM/2 - y)/(DIM/2);cuComplex c(-0.8, 0.156);cuComplex a(jx, jy);int i = 0;for (i=0; i<200; i++) {a = a * a + c;if (a.magnitude2() > 1000)return 0;}return 1;
}__global__ void kernel( unsigned char *ptr ) {// map from blockIdx to pixel positionint x = blockIdx.x;int y = blockIdx.y;int offset = x + y * gridDim.x;// now calculate the value at that positionint juliaValue = julia( x, y );ptr[offset*4 + 0] = 255 * juliaValue;ptr[offset*4 + 1] = 0;ptr[offset*4 + 2] = 0;ptr[offset*4 + 3] = 255;
}// globals needed by the update routine
struct DataBlock {unsigned char   *dev_bitmap;
};int main( void ) {DataBlock   data;CPUBitmap bitmap( DIM, DIM, &data );unsigned char    *dev_bitmap;cudaMalloc( (void**)&dev_bitmap, bitmap.image_size() );data.dev_bitmap = dev_bitmap;dim3 grid(DIM,DIM);kernel<<<grid,1>>>(dev_bitmap);cudaMemcpy(bitmap.get_ptr(), dev_bitmap, bitmap.image_size(), cudaMemcpyDeviceToHost);cudaFree(dev_bitmap);bitmap.display_and_exit();
}

编译，运行：

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CUDA 学习（CUDA实战第四章）

1.矢量求和

1.1 CPU

1.2 GPU

1.3 GPU （数据大）

2. Julia集曲线

2.1 CPU

2.2 GPU

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CUDA 学习（CUDA实战 第四章）

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2. Julia集曲线

2.1 CPU

2.2 GPU

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