我正在阅读和测试“Cuda By example. An Introduction to General Purpose GPU Programming”一书中的示例。在测试第 7 章中的示例时，相对于纹理内存，我意识到通过纹理缓存访问全局内存比直接访问要慢得多（我的 NVIDIA GPU 是 GeForceGTX 260，计算能力 1.3，我使用的是 NVDIA CUDA 4.2）：
- 256*256 图像的纹理提取（1D 或 2D）的每帧时间：93 毫秒
- 256*256 不使用纹理（仅直接全局访问）的每帧时间：8.5 毫秒
我已经仔细检查了几次代码，我也一直在阅读 SDK 随附的“CUDA C 编程指南”和“CUDA C 最佳实践指南”，但我并不真正理解问题所在。据我了解，纹理内存只是具有特定访问机制实现的全局内存，使其看起来像缓存（？）。我想知道对全局内存的合并访问是否会使纹理获取速度变慢，但我不能确定。
有没有人有类似的问题？（我在 NVIDIA 论坛中找到了一些类似问题的链接，但该链接不再可用。）
测试代码看起来是这样的，只包括相关部分：
//#define TEXTURE
//#define TEXTURE2
#ifdef TEXTURE
// According to C programming guide, it should be static (3.2.10.1.1)
static texture<float> texConstSrc;
static texture<float> texIn;
static texture<float> texOut;
#endif
__global__ void copy_const_kernel( float *iptr
#ifdef TEXTURE2
){
#else
,const float *cptr ) {
#endif
// map from threadIdx/BlockIdx to pixel position
int x = threadIdx.x + blockIdx.x * blockDim.x;
int y = threadIdx.y + blockIdx.y * blockDim.y;
int offset = x + y * blockDim.x * gridDim.x;
#ifdef TEXTURE2
float c = tex1Dfetch(texConstSrc,offset);
#else
float c = cptr[offset];
#endif
if ( c != 0) iptr[offset] = c;
}
__global__ void blend_kernel( float *outSrc,
#ifdef TEXTURE
bool dstOut ) {
#else
const float *inSrc ) {
#endif
// map from threadIdx/BlockIdx to pixel position
int x = threadIdx.x + blockIdx.x * blockDim.x;
int y = threadIdx.y + blockIdx.y * blockDim.y;
int offset = x + y * blockDim.x * gridDim.x;
int left = offset - 1;
int right = offset + 1;
if (x == 0) left++;
if (x == SXRES-1) right--;
int top = offset - SYRES;
int bottom = offset + SYRES;
if (y == 0) top += SYRES;
if (y == SYRES-1) bottom -= SYRES;
#ifdef TEXTURE
float t, l, c, r, b;
if (dstOut) {
t = tex1Dfetch(texIn,top);
l = tex1Dfetch(texIn,left);
c = tex1Dfetch(texIn,offset);
r = tex1Dfetch(texIn,right);
b = tex1Dfetch(texIn,bottom);
} else {
t = tex1Dfetch(texOut,top);
l = tex1Dfetch(texOut,left);
c = tex1Dfetch(texOut,offset);
r = tex1Dfetch(texOut,right);
b = tex1Dfetch(texOut,bottom);
}
outSrc[offset] = c + SPEED * (t + b + r + l - 4 * c);
#else
outSrc[offset] = inSrc[offset] + SPEED * ( inSrc[top] +
inSrc[bottom] + inSrc[left] + inSrc[right] -
inSrc[offset]*4);
#endif
}
// globals needed by the update routine
struct DataBlock {
unsigned char *output_bitmap;
float *dev_inSrc;
float *dev_outSrc;
float *dev_constSrc;
cudaEvent_t start, stop;
float totalTime;
float frames;
unsigned size;
unsigned char *output_host;
};
void anim_gpu( DataBlock *d, int ticks ) {
checkCudaErrors( cudaEventRecord( d->start, 0 ) );
dim3 blocks(SXRES/16,SYRES/16);
dim3 threads(16,16);
#ifdef TEXTURE
volatile bool dstOut = true;
#endif
for (int i=0; i<90; i++) {
#ifdef TEXTURE
float *in, *out;
if (dstOut) {
in = d->dev_inSrc;
out = d->dev_outSrc;
} else {
out = d->dev_inSrc;
in = d->dev_outSrc;
}
#ifdef TEXTURE2
copy_const_kernel<<<blocks,threads>>>( in );
#else
copy_const_kernel<<<blocks,threads>>>( in,
d->dev_constSrc );
#endif
blend_kernel<<<blocks,threads>>>( out, dstOut );
dstOut = !dstOut;
#else
copy_const_kernel<<<blocks,threads>>>( d->dev_inSrc,
d->dev_constSrc );
blend_kernel<<<blocks,threads>>>( d->dev_outSrc,
d->dev_inSrc );
swap( d->dev_inSrc, d->dev_outSrc );
#endif
}
// Some stuff for the events
// ...
}