reduction at the end of a 2D kernel

Accelerated Computing CUDA CUDA Programming and Performance
1

Just to check if someone maybe knows the answer.

I have a kernel with a 2D blocksize. In the first part each thread calculates some values (dependent on text2D(texref, threadIdx.x, threadIdx.y)). These values are stored to some shared arrays and in the end I need to calculate the sum, so I have to do a reduction. But I don’t know how to use the if threadIdx.x < 32 trick from the reduction example.

I think the following should work, but I am not sure how threads from a 2D block are divided into warps. The important line is unsigned int tid = threadIdx.x + __umul24(threadIdx.y, blockDim.x);, I assume tid = [0 31] are the first warp.

mykernel<<<gridsize, dim3(16,8,1)>>>(out1, out2, out3, out4, offsetx, offsety);

__global__ void mykernel(float *out1, float *out2, float *out3, float *out4, int offset1, int offset2) {

__shared__ float arr1[16*8];

__shared__ float arr2[16*8];

__shared__ float arr3[16*8];

__shared__ float arr4[16*8];

unsigned int tid = threadIdx.x + __umul24(threadIdx.y, blockDim.x);

float dum = tex2D(texref, threadIdx.x+offset1, threadIdx.y+offset2);

arr1[tid] = func1(dum);

arr2[tid] = func2(dum);

arr3[tid] = func3(dum);

arr4[tid] = func4(dum);

// now I need to do a reduction

if (tid < 64) {

  arr1[tid] += arr1[tid+64];

  arr2[tid] += arr2[tid+64];

  arr3[tid] += arr3[tid+64];

  arr4[tid] += arr4[tid+64];

}

__syncthreads();

if (tid < 32) {

  arr1[tid] += arr1[tid+32];

  arr2[tid] += arr2[tid+32];

  arr3[tid] += arr3[tid+32];

  arr4[tid] += arr4[tid+32];

 arr1[tid] += arr1[tid+16];

  arr2[tid] += arr2[tid+16];

  arr3[tid] += arr3[tid+16];

  arr4[tid] += arr4[tid+16];

 arr1[tid] += arr1[tid+8];

  arr2[tid] += arr2[tid+8];

  arr3[tid] += arr3[tid+8];

  arr4[tid] += arr4[tid+8];

 arr1[tid] += arr1[tid+4];

  arr2[tid] += arr2[tid+4];

  arr3[tid] += arr3[tid+4];

  arr4[tid] += arr4[tid+4];

 arr1[tid] += arr1[tid+2];

  arr2[tid] += arr2[tid+2];

  arr3[tid] += arr3[tid+2];

  arr4[tid] += arr4[tid+2];

 arr1[tid] += arr1[tid+1];

  arr2[tid] += arr2[tid+1];

  arr3[tid] += arr3[tid+1];

  arr4[tid] += arr4[tid+1];

}

if (tid==0) {

  out1[blockIdx.x] += arr1[0];

  out2[blockIdx.x] += arr2[0];

  out3[blockIdx.x] += arr3[0];

  out4[blockIdx.x] += arr4[0];

}

}

Does anybody have any experience with how threads are split up in warps for 2D blocksize??

2

Cuda programming guide, section 2.2.1

So, I see no reason why what you are doing shouldn’t work. Are you having a particular problem with it?

3

Well, my only problem is that I don’t read the programming guide… :">

Actually I saw the post about order of thread-execution when thinking about how to ‘solve’ my problem. So then I started to write before reading the programming guide. Soon we will have CUDA on vista, so I can do some non-thought-experiments when at home, and I will not post these kind of questions anymore. :D

4

No problem. That particular bit of information isn’t in the most obvious of places to look for it, being in the introduction section rather than in part of the reference.