Abstract This blog will try to improve the performance of previous reduction algorithm. Specifically, the strategy of removing unnecessary modular arithmetic will be discussed.
1. Modular arithmetic The operation of modular arithmetic is costly referring to wiki. To avoid that problem, we may think that could it possible for us to implement our algorithm in a more efficient way?
2. Another Way to Implement Sure in this case, the answer is yes. We reorganize our key codes as follows.
// reduction
for (int i=1; i < 1024; i *= 2){
int ntid = 2 * i * tid;
if(ntid < 1024){
data[ntid] += data[ntid + i];
}
__syncthreads();
}
A operation diagram is presented to explain these codes figuratively as follows.
3. Experimental Results
The experimental results show that the total time CUDA kernel used is 12.304 ms, which is faster than the previous implementation.
4. More The source code can be visit on github.
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